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Summarize the abstract of the paper: | Title: Why Are You Wrong? Counterfactual Explanations for Language Grounding with 3D Objects
Abstract: Combining natural language and geometric shapes is an emerging research area with multiple applications in robotics and language-assisted design. A crucial task in this domain is object referent identification, which ... | Combining natural language and geometric shapes is an emerging research area with multiple applications in robotics and language-assisted design. A crucial task in this domain is object referent ident... |
Summarize the abstract of the paper: | Title: BodyGPS: Anatomical Positioning System
Abstract: We introduce a new type of foundational model for parsing human anatomy in medical images that works for different modalities. It supports supervised or unsupervised training and can perform matching, registration, classification, or segmentation with or without u... | We introduce a new type of foundational model for parsing human anatomy in medical images that works for different modalities. It supports supervised or unsupervised training and can perform matching,... |
Summarize the abstract of the paper: | Title: Research on Anomaly Detection Methods Based on Diffusion Models
Abstract: Anomaly detection is a fundamental task in machine learning and data mining, with significant applications in cybersecurity, industrial fault diagnosis, and clinical disease monitoring. Traditional methods, such as statistical modeling and... | Anomaly detection is a fundamental task in machine learning and data mining, with significant applications in cybersecurity, industrial fault diagnosis, and clinical disease monitoring. Traditional me... |
Summarize the abstract of the paper: | Title: ProFashion: Prototype-guided Fashion Video Generation with Multiple Reference Images
Abstract: Fashion video generation aims to synthesize temporally consistent videos from reference images of a designated character. Despite significant progress, existing diffusion-based methods only support a single reference i... | Fashion video generation aims to synthesize temporally consistent videos from reference images of a designated character. Despite significant progress, existing diffusion-based methods only support a ... |
Summarize the abstract of the paper: | Title: ORL-LDM: Offline Reinforcement Learning Guided Latent Diffusion Model Super-Resolution Reconstruction
Abstract: With the rapid advancement of remote sensing technology, super-resolution image reconstruction is of great research and practical significance. Existing deep learning methods have made progress but sti... | With the rapid advancement of remote sensing technology, super-resolution image reconstruction is of great research and practical significance. Existing deep learning methods have made progress but st... |
Summarize the abstract of the paper: | Title: Rebalancing Contrastive Alignment with Learnable Semantic Gaps in Text-Video Retrieval
Abstract: Recent advances in text-video retrieval have been largely driven by contrastive learning frameworks. However, existing methods overlook a key source of optimization tension: the separation between text and video dist... | Recent advances in text-video retrieval have been largely driven by contrastive learning frameworks. However, existing methods overlook a key source of optimization tension: the separation between tex... |
Summarize the abstract of the paper: | Title: Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation
Abstract: Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance approaches, such as segmentation maps and d... | Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance approaches, such as ... |
Summarize the abstract of the paper: | Title: Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Abstract: Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-understandable concepts. However,... | Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-understandable conce... |
Summarize the abstract of the paper: | Title: Why 1 + 1 < 1 in Visual Token Pruning: Beyond Naive Integration via Multi-Objective Balanced Covering
Abstract: Existing visual token pruning methods target prompt alignment and visual preservation with static strategies, overlooking the varying relative importance of these objectives across tasks, which leads t... | Existing visual token pruning methods target prompt alignment and visual preservation with static strategies, overlooking the varying relative importance of these objectives across tasks, which leads ... |
Summarize the abstract of the paper: | Title: Lightweight Multispectral Crop-Weed Segmentation for Precision Agriculture
Abstract: Efficient crop-weed segmentation is critical for site-specific weed control in precision agriculture. Conventional CNN-based methods struggle to generalize and rely on RGB imagery, limiting performance under complex field condit... | Efficient crop-weed segmentation is critical for site-specific weed control in precision agriculture. Conventional CNN-based methods struggle to generalize and rely on RGB imagery, limiting performanc... |
Summarize the abstract of the paper: | Title: Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?
Abstract: The 180x360 omnidirectional field of view captured by 360-degree cameras enables their use in a wide range of applications such as embodied AI and virtual reality. Although recent advances in multimodal large language mod... | The 180x360 omnidirectional field of view captured by 360-degree cameras enables their use in a wide range of applications such as embodied AI and virtual reality. Although recent advances in multimod... |
Summarize the abstract of the paper: | Title: Cross-Model Transfer of Task Vectors via Few-Shot Orthogonal Alignment
Abstract: Task arithmetic enables efficient model editing by representing task-specific changes as vectors in parameter space. Task arithmetic typically assumes that the source and target models are initialized from the same pre-trained param... | Task arithmetic enables efficient model editing by representing task-specific changes as vectors in parameter space. Task arithmetic typically assumes that the source and target models are initialized... |
Summarize the abstract of the paper: | Title: Achieving 3D Attention via Triplet Squeeze and Excitation Block
Abstract: The emergence of ConvNeXt and its variants has reaffirmed the conceptual and structural suitability of CNN-based models for vision tasks, re-establishing them as key players in image classification in general, and in facial expression reco... | The emergence of ConvNeXt and its variants has reaffirmed the conceptual and structural suitability of CNN-based models for vision tasks, re-establishing them as key players in image classification in... |
Summarize the abstract of the paper: | Title: DFA-CON: A Contrastive Learning Approach for Detecting Copyright Infringement in DeepFake Art
Abstract: Recent proliferation of generative AI tools for visual content creation-particularly in the context of visual artworks-has raised serious concerns about copyright infringement and forgery. The large-scale data... | Recent proliferation of generative AI tools for visual content creation-particularly in the context of visual artworks-has raised serious concerns about copyright infringement and forgery. The large-s... |
Summarize the abstract of the paper: | Title: Industry-focused Synthetic Segmentation Pre-training
Abstract: Pre-training on real-image datasets has been widely proven effective for improving instance segmentation. However, industrial applications face two key challenges: (1) legal and ethical restrictions, such as ImageNet's prohibition of commercial use, ... | Pre-training on real-image datasets has been widely proven effective for improving instance segmentation. However, industrial applications face two key challenges: (1) legal and ethical restrictions, ... |
Summarize the abstract of the paper: | Title: Monocular Online Reconstruction with Enhanced Detail Preservation
Abstract: We propose an online 3D Gaussian-based dense mapping framework for photorealistic details reconstruction from a monocular image stream. Our approach addresses two key challenges in monocular online reconstruction: distributing Gaussians ... | We propose an online 3D Gaussian-based dense mapping framework for photorealistic details reconstruction from a monocular image stream. Our approach addresses two key challenges in monocular online re... |
Summarize the abstract of the paper: | Title: FEALLM: Advancing Facial Emotion Analysis in Multimodal Large Language Models with Emotional Synergy and Reasoning
Abstract: Facial Emotion Analysis (FEA) plays a crucial role in visual affective computing, aiming to infer a person's emotional state based on facial data. Scientifically, facial expressions (FEs) ... | Facial Emotion Analysis (FEA) plays a crucial role in visual affective computing, aiming to infer a person's emotional state based on facial data. Scientifically, facial expressions (FEs) result from ... |
Summarize the abstract of the paper: | Title: Classifying Shelf Life Quality of Pineapples by Combining Audio and Visual Features
Abstract: Determining the shelf life quality of pineapples using non-destructive methods is a crucial step to reduce waste and increase income. In this paper, a multimodal and multiview classification model was constructed to cla... | Determining the shelf life quality of pineapples using non-destructive methods is a crucial step to reduce waste and increase income. In this paper, a multimodal and multiview classification model was... |
Summarize the abstract of the paper: | Title: TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset
Abstract: Urban Digital Twins (UDTs) have become essential for managing cities and integrating complex, heterogeneous data from diverse sources. Creating UDTs involves challenges at multiple process stages, including acquiring ... | Urban Digital Twins (UDTs) have become essential for managing cities and integrating complex, heterogeneous data from diverse sources. Creating UDTs involves challenges at multiple process stages, inc... |
Summarize the abstract of the paper: | Title: CAD-Coder:Text-Guided CAD Files Code Generation
Abstract: Computer-aided design (CAD) is a way to digitally create 2D drawings and 3D models of real-world products. Traditional CAD typically relies on hand-drawing by experts or modifications of existing library files, which doesn't allow for rapid personalizatio... | Computer-aided design (CAD) is a way to digitally create 2D drawings and 3D models of real-world products. Traditional CAD typically relies on hand-drawing by experts or modifications of existing libr... |
Summarize the abstract of the paper: | Title: When Dance Video Archives Challenge Computer Vision
Abstract: The accuracy and efficiency of human body pose estimation depend on the quality of the data to be processed and of the particularities of these data. To demonstrate how dance videos can challenge pose estimation techniques, we proposed a new 3D human ... | The accuracy and efficiency of human body pose estimation depend on the quality of the data to be processed and of the particularities of these data. To demonstrate how dance videos can challenge pose... |
Summarize the abstract of the paper: | Title: Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
Abstract: As the size of large language models grows exponentially, GPU memory has become a bottleneck for adapting these models to downstream tasks. In this paper, we aim to push the limits of memory-efficient training by minimizing memory usa... | As the size of large language models grows exponentially, GPU memory has become a bottleneck for adapting these models to downstream tasks. In this paper, we aim to push the limits of memory-efficient... |
Summarize the abstract of the paper: | Title: SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation
Abstract: Data augmentation for domain-specific image classification tasks often struggles to simultaneously address diversity, faithfulness, and label clarity of generated data, leading to suboptimal performance in d... | Data augmentation for domain-specific image classification tasks often struggles to simultaneously address diversity, faithfulness, and label clarity of generated data, leading to suboptimal performan... |
Summarize the abstract of the paper: | Title: MultiLink: Multi-class Structure Recovery via Agglomerative Clustering and Model Selection
Abstract: We address the problem of recovering multiple structures of different classes in a dataset contaminated by noise and outliers. In particular, we consider geometric structures defined by a mixture of underlying pa... | We address the problem of recovering multiple structures of different classes in a dataset contaminated by noise and outliers. In particular, we consider geometric structures defined by a mixture of u... |
Summarize the abstract of the paper: | Title: Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning
Abstract: Few-shot adaptation remains a core challenge for vision-language models (VLMs), especially under limited supervision and noisy support samples. We propose PromptFuseNL, a unified framework that enhances few-... | Few-shot adaptation remains a core challenge for vision-language models (VLMs), especially under limited supervision and noisy support samples. We propose PromptFuseNL, a unified framework that enhanc... |
Summarize the abstract of the paper: | Title: Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena
Abstract: Wasserstein distances provide a powerful framework for comparing data distributions. They can be used to analyze processes over time or to detect inhomogeneities within data. However, simply calculating the Was... | Wasserstein distances provide a powerful framework for comparing data distributions. They can be used to analyze processes over time or to detect inhomogeneities within data. However, simply calculati... |
Summarize the abstract of the paper: | Title: Enabling Privacy-Aware AI-Based Ergonomic Analysis
Abstract: Musculoskeletal disorders (MSDs) are a leading cause of injury and productivity loss in the manufacturing industry, incurring substantial economic costs. Ergonomic assessments can mitigate these risks by identifying workplace adjustments that improve p... | Musculoskeletal disorders (MSDs) are a leading cause of injury and productivity loss in the manufacturing industry, incurring substantial economic costs. Ergonomic assessments can mitigate these risks... |
Summarize the abstract of the paper: | Title: Human Motion Prediction via Test-domain-aware Adaptation with Easily-available Human Motions Estimated from Videos
Abstract: In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits the data... | In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits the data diversity, ... |
Summarize the abstract of the paper: | Title: Visual Watermarking in the Era of Diffusion Models: Advances and Challenges
Abstract: As generative artificial intelligence technologies like Stable Diffusion advance, visual content becomes more vulnerable to misuse, raising concerns about copyright infringement. Visual watermarks serve as effective protection ... | As generative artificial intelligence technologies like Stable Diffusion advance, visual content becomes more vulnerable to misuse, raising concerns about copyright infringement. Visual watermarks ser... |
Summarize the abstract of the paper: | Title: Hybrid Spiking Vision Transformer for Object Detection with Event Cameras
Abstract: Event-based object detection has gained increasing attention due to its advantages such as high temporal resolution, wide dynamic range, and asynchronous address-event representation. Leveraging these advantages, Spiking Neural N... | Event-based object detection has gained increasing attention due to its advantages such as high temporal resolution, wide dynamic range, and asynchronous address-event representation. Leveraging these... |
Summarize the abstract of the paper: | Title: A portable diagnosis model for Keratoconus using a smartphone
Abstract: Keratoconus (KC) is a corneal disorder that results in blurry and distorted vision. Traditional diagnostic tools, while effective, are often bulky, costly, and require professional operation. In this paper, we present a portable and innovati... | Keratoconus (KC) is a corneal disorder that results in blurry and distorted vision. Traditional diagnostic tools, while effective, are often bulky, costly, and require professional operation. In this ... |
Summarize the abstract of the paper: | Title: Decoupled Multimodal Prototypes for Visual Recognition with Missing Modalities
Abstract: Multimodal learning enhances deep learning models by enabling them to perceive and understand information from multiple data modalities, such as visual and textual inputs. However, most existing approaches assume the availab... | Multimodal learning enhances deep learning models by enabling them to perceive and understand information from multiple data modalities, such as visual and textual inputs. However, most existing appro... |
Summarize the abstract of the paper: | Title: ADD: Physics-Based Motion Imitation with Adversarial Differential Discriminators
Abstract: Multi-objective optimization problems, which require the simultaneous optimization of multiple terms, are prevalent across numerous applications. Existing multi-objective optimization methods often rely on manually tuned a... | Multi-objective optimization problems, which require the simultaneous optimization of multiple terms, are prevalent across numerous applications. Existing multi-objective optimization methods often re... |
Summarize the abstract of the paper: | Title: Thermal Detection of People with Mobility Restrictions for Barrier Reduction at Traffic Lights Controlled Intersections
Abstract: Rapid advances in deep learning for computer vision have driven the adoption of RGB camera-based adaptive traffic light systems to improve traffic safety and pedestrian comfort. Howev... | Rapid advances in deep learning for computer vision have driven the adoption of RGB camera-based adaptive traffic light systems to improve traffic safety and pedestrian comfort. However, these systems... |
Summarize the abstract of the paper: | Title: LightLab: Controlling Light Sources in Images with Diffusion Models
Abstract: We present a simple, yet effective diffusion-based method for fine-grained, parametric control over light sources in an image. Existing relighting methods either rely on multiple input views to perform inverse rendering at inference ti... | We present a simple, yet effective diffusion-based method for fine-grained, parametric control over light sources in an image. Existing relighting methods either rely on multiple input views to perfor... |
Summarize the abstract of the paper: | Title: Open-Source Multi-Viewpoint Surgical Telerobotics
Abstract: As robots for minimally invasive surgery (MIS) gradually become more accessible and modular, we believe there is a great opportunity to rethink and expand the visualization and control paradigms that have characterized surgical teleoperation since its i... | As robots for minimally invasive surgery (MIS) gradually become more accessible and modular, we believe there is a great opportunity to rethink and expand the visualization and control paradigms that ... |
Summarize the abstract of the paper: | Title: MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learning
Abstract: Visible and infrared image fusion (VIF) has attracted significant attention in recent years. Traditional VIF methods primarily focus on generating fused images with high visual quality, while recent advancemen... | Visible and infrared image fusion (VIF) has attracted significant attention in recent years. Traditional VIF methods primarily focus on generating fused images with high visual quality, while recent a... |
Summarize the abstract of the paper: | Title: HMPNet: A Feature Aggregation Architecture for Maritime Object Detection from a Shipborne Perspective
Abstract: In the realm of intelligent maritime navigation, object detection from a shipborne perspective is paramount. Despite the criticality, the paucity of maritime-specific data impedes the deployment of sop... | In the realm of intelligent maritime navigation, object detection from a shipborne perspective is paramount. Despite the criticality, the paucity of maritime-specific data impedes the deployment of so... |
Summarize the abstract of the paper: | Title: Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes
Abstract: Kolmogorov-Arnold Networks (KAN) offer universal function approximation using univariate spline compositions without nonlinear activations. In this work, we integrate Error-Correcting Output Codes (ECOC) into the... | Kolmogorov-Arnold Networks (KAN) offer universal function approximation using univariate spline compositions without nonlinear activations. In this work, we integrate Error-Correcting Output Codes (EC... |
Summarize the abstract of the paper: | Title: Learning to Adapt to Position Bias in Vision Transformer Classifiers
Abstract: How discriminative position information is for image classification depends on the data. On the one hand, the camera position is arbitrary and objects can appear anywhere in the image, arguing for translation invariance. At the same t... | How discriminative position information is for image classification depends on the data. On the one hand, the camera position is arbitrary and objects can appear anywhere in the image, arguing for tra... |
Summarize the abstract of the paper: | Title: BiECVC: Gated Diversification of Bidirectional Contexts for Learned Video Compression
Abstract: Recent forward prediction-based learned video compression (LVC) methods have achieved impressive results, even surpassing VVC reference software VTM under the Low Delay B (LDB) configuration. In contrast, learned bidi... | Recent forward prediction-based learned video compression (LVC) methods have achieved impressive results, even surpassing VVC reference software VTM under the Low Delay B (LDB) configuration. In contr... |
Summarize the abstract of the paper: | Title: A generalisable head MRI defacing pipeline: Evaluation on 2,566 meningioma scans
Abstract: Reliable MRI defacing techniques to safeguard patient privacy while preserving brain anatomy are critical for research collaboration. Existing methods often struggle with incomplete defacing or degradation of brain tissue ... | Reliable MRI defacing techniques to safeguard patient privacy while preserving brain anatomy are critical for research collaboration. Existing methods often struggle with incomplete defacing or degrad... |
Summarize the abstract of the paper: | Title: EnerVerse-AC: Envisioning Embodied Environments with Action Condition
Abstract: Robotic imitation learning has advanced from solving static tasks to addressing dynamic interaction scenarios, but testing and evaluation remain costly and challenging due to the need for real-time interaction with dynamic environmen... | Robotic imitation learning has advanced from solving static tasks to addressing dynamic interaction scenarios, but testing and evaluation remain costly and challenging due to the need for real-time in... |
Summarize the abstract of the paper: | Title: A Preliminary Study for GPT-4o on Image Restoration
Abstract: OpenAI's GPT-4o model, integrating multi-modal inputs and outputs within an autoregressive architecture, has demonstrated unprecedented performance in image generation. In this work, we investigate its potential impact on the image restoration communi... | OpenAI's GPT-4o model, integrating multi-modal inputs and outputs within an autoregressive architecture, has demonstrated unprecedented performance in image generation. In this work, we investigate it... |
Summarize the abstract of the paper: | Title: VoiceCloak: A Multi-Dimensional Defense Framework against Unauthorized Diffusion-based Voice Cloning
Abstract: Diffusion Models (DMs) have achieved remarkable success in realistic voice cloning (VC), while they also increase the risk of malicious misuse. Existing proactive defenses designed for traditional VC mo... | Diffusion Models (DMs) have achieved remarkable success in realistic voice cloning (VC), while they also increase the risk of malicious misuse. Existing proactive defenses designed for traditional VC ... |
Summarize the abstract of the paper: | Title: Selftok: Discrete Visual Tokens of Autoregression, by Diffusion, and for Reasoning
Abstract: We completely discard the conventional spatial prior in image representation and introduce a novel discrete visual tokenizer: Self-consistency Tokenizer (Selftok). At its design core, we compose an autoregressive (AR) pr... | We completely discard the conventional spatial prior in image representation and introduce a novel discrete visual tokenizer: Self-consistency Tokenizer (Selftok). At its design core, we compose an au... |
Summarize the abstract of the paper: | Title: VALISENS: A Validated Innovative Multi-Sensor System for Cooperative Automated Driving
Abstract: Perception is a core capability of automated vehicles and has been significantly advanced through modern sensor technologies and artificial intelligence. However, perception systems still face challenges in complex r... | Perception is a core capability of automated vehicles and has been significantly advanced through modern sensor technologies and artificial intelligence. However, perception systems still face challen... |
Summarize the abstract of the paper: | Title: Enhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?
Abstract: Diffusion MRI (dMRI) is essential for studying brain microstructure, but high-resolution imaging remains challenging due to the inherent trade-offs between acquisition time and signal... | Diffusion MRI (dMRI) is essential for studying brain microstructure, but high-resolution imaging remains challenging due to the inherent trade-offs between acquisition time and signal-to-noise ratio (... |
Summarize the abstract of the paper: | Title: ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models
Abstract: Chart understanding presents a unique challenge for large vision-language models (LVLMs), as it requires the integration of sophisticated textual and visual reasoning capabilities. However, current LVLMs exhibit a notabl... | Chart understanding presents a unique challenge for large vision-language models (LVLMs), as it requires the integration of sophisticated textual and visual reasoning capabilities. However, current LV... |
Summarize the abstract of the paper: | Title: MASSV: Multimodal Adaptation and Self-Data Distillation for Speculative Decoding of Vision-Language Models
Abstract: Speculative decoding significantly accelerates language model inference by enabling a lightweight draft model to propose multiple tokens that a larger target model verifies simultaneously. However... | Speculative decoding significantly accelerates language model inference by enabling a lightweight draft model to propose multiple tokens that a larger target model verifies simultaneously. However, ap... |
Summarize the abstract of the paper: | Title: Just Dance with $ $! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection
Abstract: Weakly-supervised methods for video anomaly detection (VAD) are conventionally based merely on RGB spatio-temporal features, which continues to limit their reliability in real-world scenarios. This is due to the fa... | Weakly-supervised methods for video anomaly detection (VAD) are conventionally based merely on RGB spatio-temporal features, which continues to limit their reliability in real-world scenarios. This is... |
Summarize the abstract of the paper: | Title: Generative AI for Autonomous Driving: Frontiers and Opportunities
Abstract: Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation, reasoning, planning, and multimodal understanding. This r... | Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation, reasoning, planning,... |
Summarize the abstract of the paper: | Title: FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation
Abstract: This paper investigates training better visual world models for robot manipulation, i.e., models that can predict future visual observations by conditioning on past frames and robot actions. Specifically, we ... | This paper investigates training better visual world models for robot manipulation, i.e., models that can predict future visual observations by conditioning on past frames and robot actions. Specifica... |
Summarize the abstract of the paper: | Title: Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging
Abstract: Advances in medical imaging and deep learning have propelled progress in whole slide image (WSI) analysis, with multiple instance learning (MIL) showing promise for efficient and accurate diagnostics. However, conventi... | Advances in medical imaging and deep learning have propelled progress in whole slide image (WSI) analysis, with multiple instance learning (MIL) showing promise for efficient and accurate diagnostics.... |
Summarize the abstract of the paper: | Title: ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
Abstract: Pruning is a widely used method for compressing Deep Neural Networks (DNNs), where less relevant parameters are removed from a DNN model to reduce its size. However, removing parameters reduces model accuracy, so pruning... | Pruning is a widely used method for compressing Deep Neural Networks (DNNs), where less relevant parameters are removed from a DNN model to reduce its size. However, removing parameters reduces model ... |
Summarize the abstract of the paper: | Title: SPKLIP: Aligning Spike Video Streams with Natural Language
Abstract: Spike cameras offer unique sensing capabilities but their sparse, asynchronous output challenges semantic understanding, especially for Spike Video-Language Alignment (Spike-VLA) where models like CLIP underperform due to modality mismatch. We ... | Spike cameras offer unique sensing capabilities but their sparse, asynchronous output challenges semantic understanding, especially for Spike Video-Language Alignment (Spike-VLA) where models like CLI... |
Summarize the abstract of the paper: | Title: PRE-Mamba: A 4D State Space Model for Ultra-High-Frequent Event Camera Deraining
Abstract: Event cameras excel in high temporal resolution and dynamic range but suffer from dense noise in rainy conditions. Existing event deraining methods face trade-offs between temporal precision, deraining effectiveness, and c... | Event cameras excel in high temporal resolution and dynamic range but suffer from dense noise in rainy conditions. Existing event deraining methods face trade-offs between temporal precision, derainin... |
Summarize the abstract of the paper: | Title: A Reproduction Study: The Kernel PCA Interpretation of Self-Attention Fails Under Scrutiny
Abstract: In this reproduction study, we revisit recent claims that self-attention implements kernel principal component analysis (KPCA) (Teo et al., 2024), positing that (i) value vectors $V$ capture the eigenvectors of t... | In this reproduction study, we revisit recent claims that self-attention implements kernel principal component analysis (KPCA) (Teo et al., 2024), positing that (i) value vectors $V$ capture the eigen... |
Summarize the abstract of the paper: | Title: Dynam3D: Dynamic Layered 3D Tokens Empower VLM for Vision-and-Language Navigation
Abstract: Vision-and-Language Navigation (VLN) is a core task where embodied agents leverage their spatial mobility to navigate in 3D environments toward designated destinations based on natural language instructions. Recently, vid... | Vision-and-Language Navigation (VLN) is a core task where embodied agents leverage their spatial mobility to navigate in 3D environments toward designated destinations based on natural language instru... |
Summarize the abstract of the paper: | Title: GNCAF: A GNN-based Neighboring Context Aggregation Framework for Tertiary Lymphoid Structures Semantic Segmentation in WSI
Abstract: Tertiary lymphoid structures (TLS) are organized clusters of immune cells, whose maturity and area can be quantified in whole slide image (WSI) for various prognostic tasks. Existi... | Tertiary lymphoid structures (TLS) are organized clusters of immune cells, whose maturity and area can be quantified in whole slide image (WSI) for various prognostic tasks. Existing methods for asses... |
Summarize the abstract of the paper: | Title: MARRS: Masked Autoregressive Unit-based Reaction Synthesis
Abstract: This work aims at a challenging task: human action-reaction synthesis, i.e., generating human reactions based on the action sequence of the other as conditions. Currently, autoregressive modeling approaches have achieved remarkable performance ... | This work aims at a challenging task: human action-reaction synthesis, i.e., generating human reactions based on the action sequence of the other as conditions. Currently, autoregressive modeling appr... |
Summarize the abstract of the paper: | Title: Emergence of Fixational and Saccadic Movements in a Multi-Level Recurrent Attention Model for Vision
Abstract: Inspired by foveal vision, hard attention models promise interpretability and parameter economy. However, existing models like the Recurrent Model of Visual Attention (RAM) and Deep Recurrent Attention ... | Inspired by foveal vision, hard attention models promise interpretability and parameter economy. However, existing models like the Recurrent Model of Visual Attention (RAM) and Deep Recurrent Attentio... |
Summarize the abstract of the paper: | Title: TUGS: Physics-based Compact Representation of Underwater Scenes by Tensorized Gaussian
Abstract: Underwater 3D scene reconstruction is crucial for undewater robotic perception and navigation. However, the task is significantly challenged by the complex interplay between light propagation, water medium, and objec... | Underwater 3D scene reconstruction is crucial for undewater robotic perception and navigation. However, the task is significantly challenged by the complex interplay between light propagation, water m... |
Summarize the abstract of the paper: | Title: A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios
Abstract: Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metric localization tasks to achieve fine-grained predi... | Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metric localization tasks to achieve fine-grained predict... |
Summarize the abstract of the paper: | Title: Overview of the NLPCC 2025 Shared Task 4: Multi-modal, Multilingual, and Multi-hop Medical Instructional Video Question Answering Challenge
Abstract: Following the successful hosts of the 1-st (NLPCC 2023 Foshan) CMIVQA and the 2-rd (NLPCC 2024 Hangzhou) MMIVQA challenges, this year, a new task has been introduc... | Following the successful hosts of the 1-st (NLPCC 2023 Foshan) CMIVQA and the 2-rd (NLPCC 2024 Hangzhou) MMIVQA challenges, this year, a new task has been introduced to further advance research in mul... |
Summarize the abstract of the paper: | Title: Predicting Risk of Pulmonary Fibrosis Formation in PASC Patients
Abstract: While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly known as Long COVID. There remains substantial uncertainty regarding both its duration and... | While the acute phase of the COVID-19 pandemic has subsided, its long-term effects persist through Post-Acute Sequelae of COVID-19 (PASC), commonly known as Long COVID. There remains substantial uncer... |
Summarize the abstract of the paper: | Title: Camera-Only Bird's Eye View Perception: A Neural Approach to LiDAR-Free Environmental Mapping for Autonomous Vehicles
Abstract: Autonomous vehicle perception systems have traditionally relied on costly LiDAR sensors to generate precise environmental representations. In this paper, we propose a camera-only percep... | Autonomous vehicle perception systems have traditionally relied on costly LiDAR sensors to generate precise environmental representations. In this paper, we propose a camera-only perception framework ... |
Summarize the abstract of the paper: | Title: Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores
Abstract: The advent of convenient and efficient fully unmanned stores equipped with artificial intelligence-based automated checkout systems marks a new era in retail. However, these systems have inherent artificial intelligence secu... | The advent of convenient and efficient fully unmanned stores equipped with artificial intelligence-based automated checkout systems marks a new era in retail. However, these systems have inherent arti... |
Summarize the abstract of the paper: | Title: ViEEG: Hierarchical Neural Coding with Cross-Modal Progressive Enhancement for EEG-Based Visual Decoding
Abstract: Understanding and decoding brain activity into visual representations is a fundamental challenge at the intersection of neuroscience and artificial intelligence. While EEG-based visual decoding has ... | Understanding and decoding brain activity into visual representations is a fundamental challenge at the intersection of neuroscience and artificial intelligence. While EEG-based visual decoding has sh... |
Summarize the abstract of the paper: | Title: Ranking-aware Continual Learning for LiDAR Place Recognition
Abstract: Place recognition plays a significant role in SLAM, robot navigation, and autonomous driving applications. Benefiting from deep learning, the performance of LiDAR place recognition (LPR) has been greatly improved. However, many existing learn... | Place recognition plays a significant role in SLAM, robot navigation, and autonomous driving applications. Benefiting from deep learning, the performance of LiDAR place recognition (LPR) has been grea... |
Summarize the abstract of the paper: | Title: RefPose: Leveraging Reference Geometric Correspondences for Accurate 6D Pose Estimation of Unseen Objects
Abstract: Estimating the 6D pose of unseen objects from monocular RGB images remains a challenging problem, especially due to the lack of prior object-specific knowledge. To tackle this issue, we propose Ref... | Estimating the 6D pose of unseen objects from monocular RGB images remains a challenging problem, especially due to the lack of prior object-specific knowledge. To tackle this issue, we propose RefPos... |
Summarize the abstract of the paper: | Title: Metrics that matter: Evaluating image quality metrics for medical image generation
Abstract: Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for clinical applications. Standard evaluat... | Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for clinical applicatio... |
Summarize the abstract of the paper: | Title: Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis
Abstract: This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifi... | This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifical... |
Summarize the abstract of the paper: | Title: Robust Cross-View Geo-Localization via Content-Viewpoint Disentanglement
Abstract: Cross-view geo-localization (CVGL) aims to match images of the same geographic location captured from different perspectives, such as drones and satellites. Despite recent advances, CVGL remains highly challenging due to significa... | Cross-view geo-localization (CVGL) aims to match images of the same geographic location captured from different perspectives, such as drones and satellites. Despite recent advances, CVGL remains highl... |
Summarize the abstract of the paper: | Title: Active Learning for Multi-class Image Classification
Abstract: A principle bottleneck in image classification is the large number of training examples needed to train a classifier. Using active learning, we can reduce the number of training examples to teach a CNN classifier by strategically selecting examples. ... | A principle bottleneck in image classification is the large number of training examples needed to train a classifier. Using active learning, we can reduce the number of training examples to teach a CN... |
Summarize the abstract of the paper: | Title: Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Abstract: Diffusion models are widely used as priors in imaging inverse problems. However, their performance often degrades under distribution shifts between the training and test-time images. Existing methods for identifying... | Diffusion models are widely used as priors in imaging inverse problems. However, their performance often degrades under distribution shifts between the training and test-time images. Existing methods ... |
Summarize the abstract of the paper: | Title: NeuSEditor: From Multi-View Images to Text-Guided Neural Surface Edits
Abstract: Implicit surface representations are valued for their compactness and continuity, but they pose significant challenges for editing. Despite recent advancements, existing methods often fail to preserve identity and maintain geometric... | Implicit surface representations are valued for their compactness and continuity, but they pose significant challenges for editing. Despite recent advancements, existing methods often fail to preserve... |
Summarize the abstract of the paper: | Title: The City that Never Settles: Simulation-based LiDAR Dataset for Long-Term Place Recognition Under Extreme Structural Changes
Abstract: Large-scale construction and demolition significantly challenge long-term place recognition (PR) by drastically reshaping urban and suburban environments. Existing datasets predo... | Large-scale construction and demolition significantly challenge long-term place recognition (PR) by drastically reshaping urban and suburban environments. Existing datasets predominantly reflect limit... |
Summarize the abstract of the paper: | Title: Sage Deer: A Super-Aligned Driving Generalist Is Your Copilot
Abstract: The intelligent driving cockpit, an important part of intelligent driving, needs to match different users' comfort, interaction, and safety needs. This paper aims to build a Super-Aligned and GEneralist DRiving agent, SAGE DeeR. Sage Deer ac... | The intelligent driving cockpit, an important part of intelligent driving, needs to match different users' comfort, interaction, and safety needs. This paper aims to build a Super-Aligned and GEnerali... |
Summarize the abstract of the paper: | Title: Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding
Abstract: Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration of visual perception and textua... | Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration of visual perception... |
Summarize the abstract of the paper: | Title: FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance
Abstract: Despite significant advances in video generation, synthesizing physically plausible human actions remains a persistent challenge, particularly in modeling fine-grained semantics and ... | Despite significant advances in video generation, synthesizing physically plausible human actions remains a persistent challenge, particularly in modeling fine-grained semantics and complex temporal d... |
Summarize the abstract of the paper: | Title: Multi-step manipulation task and motion planning guided by video demonstration
Abstract: This work aims to leverage instructional video to solve complex multi-step task-and-motion planning tasks in robotics. Towards this goal, we propose an extension of the well-established Rapidly-Exploring Random Tree (RRT) pl... | This work aims to leverage instructional video to solve complex multi-step task-and-motion planning tasks in robotics. Towards this goal, we propose an extension of the well-established Rapidly-Explor... |
Summarize the abstract of the paper: | Title: CROC: Evaluating and Training T2I Metrics with Pseudo- and Human-Labeled Contrastive Robustness Checks
Abstract: The assessment of evaluation metrics (meta-evaluation) is crucial for determining the suitability of existing metrics in text-to-image (T2I) generation tasks. Human-based meta-evaluation is costly and... | The assessment of evaluation metrics (meta-evaluation) is crucial for determining the suitability of existing metrics in text-to-image (T2I) generation tasks. Human-based meta-evaluation is costly and... |
Summarize the abstract of the paper: | Title: Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach
Abstract: Fine-grained economic mapping through urban representation learning has emerged as a crucial tool for evidence-based economic decisions. While existing methods primarily rely on supervised or unsuper... | Fine-grained economic mapping through urban representation learning has emerged as a crucial tool for evidence-based economic decisions. While existing methods primarily rely on supervised or unsuperv... |
Summarize the abstract of the paper: | Title: BandRC: Band Shifted Raised Cosine Activated Implicit Neural Representations
Abstract: In recent years, implicit neural representations(INRs) have gained popularity in the computer vision community. This is mainly due to the strong performance of INRs in many computer vision tasks. These networks can extract a c... | In recent years, implicit neural representations(INRs) have gained popularity in the computer vision community. This is mainly due to the strong performance of INRs in many computer vision tasks. Thes... |
Summarize the abstract of the paper: | Title: Pixel Motion as Universal Representation for Robot Control
Abstract: We present LangToMo, a vision-language-action framework structured as a dual-system architecture that uses pixel motion forecasts as intermediate representations. Our high-level System 2, an image diffusion model, generates text-conditioned pix... | We present LangToMo, a vision-language-action framework structured as a dual-system architecture that uses pixel motion forecasts as intermediate representations. Our high-level System 2, an image dif... |
Summarize the abstract of the paper: | Title: Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework
Abstract: Recently, numerous pancreas segmentation methods have achieved promising performance on local single-source datasets. However, these methods don't adequately account for generalizability issues, and hence typically show l... | Recently, numerous pancreas segmentation methods have achieved promising performance on local single-source datasets. However, these methods don't adequately account for generalizability issues, and h... |
Summarize the abstract of the paper: | Title: Towards a Universal Image Degradation Model via Content-Degradation Disentanglement
Abstract: Image degradation synthesis is highly desirable in a wide variety of applications ranging from image restoration to simulating artistic effects. Existing models are designed to generate one specific or a narrow set of d... | Image degradation synthesis is highly desirable in a wide variety of applications ranging from image restoration to simulating artistic effects. Existing models are designed to generate one specific o... |
Summarize the abstract of the paper: | Title: StoryReasoning Dataset: Using Chain-of-Thought for Scene Understanding and Grounded Story Generation
Abstract: Visual storytelling systems struggle to maintain character identity across frames and link actions to appropriate subjects, frequently leading to referential hallucinations. These issues can be addresse... | Visual storytelling systems struggle to maintain character identity across frames and link actions to appropriate subjects, frequently leading to referential hallucinations. These issues can be addres... |
Summarize the abstract of the paper: | Title: Don't Forget your Inverse DDIM for Image Editing
Abstract: The field of text-to-image generation has undergone significant advancements with the introduction of diffusion models. Nevertheless, the challenge of editing real images persists, as most methods are either computationally intensive or produce poor reco... | The field of text-to-image generation has undergone significant advancements with the introduction of diffusion models. Nevertheless, the challenge of editing real images persists, as most methods are... |
Summarize the abstract of the paper: | Title: GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editing
Abstract: Scene text editing, a subfield of image editing, requires modifying texts in images while preserving style consistency and visual coherence with the surrounding environment. While diffusion-based methods have shown promise in text gener... | Scene text editing, a subfield of image editing, requires modifying texts in images while preserving style consistency and visual coherence with the surrounding environment. While diffusion-based meth... |
Summarize the abstract of the paper: | Title: Multi-modal wound classification using wound image and location by Xception and Gaussian Mixture Recurrent Neural Network (GMRNN)
Abstract: The effective diagnosis of acute and hard-to-heal wounds is crucial for wound care practitioners to provide effective patient care. Poor clinical outcomes are often linked t... | The effective diagnosis of acute and hard-to-heal wounds is crucial for wound care practitioners to provide effective patient care. Poor clinical outcomes are often linked to infection, peripheral vas... |
Summarize the abstract of the paper: | Title: AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detection
Abstract: Current multimodal large language models (MLLMs) struggle to understand circuit schematics due to their limited recognition capabilities. This could be attributed to the lack of high-quality schematic-netlist training data. Existin... | Current multimodal large language models (MLLMs) struggle to understand circuit schematics due to their limited recognition capabilities. This could be attributed to the lack of high-quality schematic... |
Summarize the abstract of the paper: | Title: Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation
Abstract: Cardiac image segmentation is an important step in many cardiac image analysis and modeling tasks such as motion tracking or simulations of cardiac mechanics. While deep learning has greatly advanced segmenta... | Cardiac image segmentation is an important step in many cardiac image analysis and modeling tasks such as motion tracking or simulations of cardiac mechanics. While deep learning has greatly advanced ... |
Summarize the abstract of the paper: | Title: VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection
Abstract: Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in environmental conditions and sensor inputs. As a result, they struggle to... | Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in environmental conditions and sensor inputs. As a res... |
Summarize the abstract of the paper: | Title: Anti-Inpainting: A Proactive Defense against Malicious Diffusion-based Inpainters under Unknown Conditions
Abstract: As diffusion-based malicious image manipulation becomes increasingly prevalent, multiple proactive defense methods are developed to safeguard images against unauthorized tampering. However, most p... | As diffusion-based malicious image manipulation becomes increasingly prevalent, multiple proactive defense methods are developed to safeguard images against unauthorized tampering. However, most proac... |
Summarize the abstract of the paper: | Title: SkillFormer: Unified Multi-View Video Understanding for Proficiency Estimation
Abstract: Assessing human skill levels in complex activities is a challenging problem with applications in sports, rehabilitation, and training. In this work, we present SkillFormer, a parameter-efficient architecture for unified mult... | Assessing human skill levels in complex activities is a challenging problem with applications in sports, rehabilitation, and training. In this work, we present SkillFormer, a parameter-efficient archi... |
Summarize the abstract of the paper: | Title: Improving Generalization of Medical Image Registration Foundation Model
Abstract: Deformable registration is a fundamental task in medical image processing, aiming to achieve precise alignment by establishing nonlinear correspondences between images. Traditional methods offer good adaptability and interpretabili... | Deformable registration is a fundamental task in medical image processing, aiming to achieve precise alignment by establishing nonlinear correspondences between images. Traditional methods offer good ... |
Summarize the abstract of the paper: | Title: Parameter Efficient Continual Learning with Dynamic Low-Rank Adaptation
Abstract: Catastrophic forgetting has remained a critical challenge for deep neural networks in Continual Learning (CL) as it undermines consolidated knowledge when learning new tasks. Parameter efficient fine tuning CL techniques are gainin... | Catastrophic forgetting has remained a critical challenge for deep neural networks in Continual Learning (CL) as it undermines consolidated knowledge when learning new tasks. Parameter efficient fine ... |
Summarize the abstract of the paper: | Title: SEAL: Searching Expandable Architectures for Incremental Learning
Abstract: Incremental learning is a machine learning paradigm where a model learns from a sequential stream of tasks. This setting poses a key challenge: balancing plasticity (learning new tasks) and stability (preserving past knowledge). Neural A... | Incremental learning is a machine learning paradigm where a model learns from a sequential stream of tasks. This setting poses a key challenge: balancing plasticity (learning new tasks) and stability ... |
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