cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12580246
title: Relationship between rupture lengths and magnitudes of oceanic transform fault earthquakes, equatorial Atlantic

description: We provide here the supplementary material to Relationship between rupture lengths and magnitudes of oceanic transform fault earthquakes, equatorial Atlantic by Guilherme de Melo, Ingo Grevemeyer, Dietrich Lange, Dirk Metz, and Heidrun Kopp.
DOI: 10.57702/goou8d72
title: Semantic3D

description: A large-scale point cloud classification benchmark, focusing on semantic segmentation of urban scenes.
DOI: 10.57702/ywijalv2
title: DFNet: Discriminative feature extraction and integration network for salient object detection

description: The proposed method for saliency detection task, which is composed of two main modules.
DOI: 10.57702/cogg6kd7
title: FGSC-23

description: Ship orientation angle prediction (SOAP) with optical remote sensing images is an important image processing task, which often relies on deep convolutional neural networks (CNNs) to make accurate predictions.
DOI: 10.57702/vi0cfnb5
title: ArtScore Dataset

description: A dataset for training the ArtScore model
DOI: 10.57702/ijlrj58x
title: Dynamic Batch Norm Statistics Update for Natural Robustness

description: CIFAR10-C and ImageNet-C datasets are used to evaluate the proposed framework for improving the natural robustness of trained DNNs against corrupted inputs.
DOI: 10.57702/o4sp24h8
title: CIFAR10 and CIFAR100 datasets

description: The CIFAR10 and CIFAR100 datasets are used to evaluate the proposed randomized defense method.
DOI: 10.57702/mw3lrv2u
title: Style Conditioned Recommendations

description: The dataset used in this paper is a user-item click matrix with item content data and item style labels.
DOI: 10.57702/2isyxjeh
title: SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model

description: Skin cancer segmentation using Segment Anything Model
DOI: 10.57702/x1udfia5
title: Spectrogram dataset for O-RAN

description: The dataset used in this paper is a collection of spectrograms, which are 2D representations of the frequency domain of RF signals.
DOI: 10.57702/h8avtdyc
title: Face Recognition Grand Challenge (FRGCv2)

description: The Face Recognition Grand Challenge (FRGCv2) dataset contains images of faces with varying lighting conditions, expressions, and poses.
DOI: 10.57702/2zmnrrrb
title: Face Research London Lab (FRLL) dataset

description: The Face Research London Lab (FRLL) dataset contains images of faces with varying lighting conditions, expressions, and poses.
DOI: 10.57702/isr5ko7f
title: SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

description: SDXL: Improving latent diffusion models for high-resolution image synthesis.
DOI: 10.57702/e3wxpdur
title: Symmetric Autoencoder for Redatuming Physical Systems

description: The dataset is used for redatuming physical systems using symmetric autoencoders. It contains seismic wave data from different states with varying nuisance parameters.
DOI: 10.57702/bvbv5g1s
title: PhotoBot: Reference-Guided Interactive Photography via Natural Language

description: PhotoBot is a framework for fully automated photo acquisition based on an interplay between high-level human language guidance and a robot photographer.
DOI: 10.57702/nctk733x
title: KITTI360

description: The KITTI360 dataset is used for evaluating the proposed Tuple-Circle loss function for cross-modality feature learning. The dataset consists of image and LiDAR scan pairs.
DOI: 10.57702/ic6i5zk1
title: MovieLens10M

description: The MovieLens10M dataset is a classic movie rating dataset, whose ratings range from 0.5 to 5.
DOI: 10.57702/6l5lbqax
title: Netflix

description: The dataset used in this paper is a large-scale dataset for implicit feedback, consisting of user-item interactions, where each interaction is a pair of a user and an item.
DOI: 10.57702/041adxuj
title: Amazon

description: The dataset used in the paper is a series of datasets introduced in [46], comprising large corpora of product reviews crawled from Amazon.com. Top-level product categories on Amazon are treated as separate datasets. We consider two categories, ‘Beauty,’ and ‘Games.’ This dataset is notable for its high sparsity and variability.
DOI: 10.57702/t3qkpe29
title: Wiki-CS

description: The dataset used in the paper to evaluate the inﬂuence of graph elements on the parameter changes of GCNs without needing to retrain the GCNs.
DOI: 10.57702/8fhn53yn
title: Amazon Photos

description: The dataset used in the paper to evaluate the inﬂuence of graph elements on the parameter changes of GCNs without needing to retrain the GCNs.
DOI: 10.57702/oer82240
title: ImageNet-Dogs

description: The dataset used in the paper for image classification, object detection, and face verification tasks.
DOI: 10.57702/btbb2gy0
title: FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis

description: FastDiff is a fast conditional diffusion model for high-quality speech synthesis. It employs a stack of time-aware location-variable convolutions with diverse receptive field patterns to model long-term time dependencies with adaptive conditions.
DOI: 10.57702/v7a23pbp
title: FastSpeech 2: Fast and High-Quality End-to-End Text-to-Speech

description: FastSpeech 2 is a fast and high-quality end-to-end text-to-speech system. It uses a multi-task learning approach to learn the mapping between phonemes and waveforms.
DOI: 10.57702/ihzrsh0m
title: LJSpeech Dataset

description: The LJSpeech dataset is a collection of audio recordings of a single female speaker reading aloud.
DOI: 10.57702/fcmb7hfq
title: VCTK Dataset

description: The VCTK dataset is a large corpus of speech recordings, each containing a single speaker and a single sentence.
DOI: 10.57702/cyr7lydz
title: GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model

description: This paper tackles a novel problem: how to transfer knowledge from the emerging Segment Anything Model (SAM) to learn a compact panoramic semantic segmentation model, i.e., student, without requiring any labeled data.
DOI: 10.57702/itycvx7y
title: Kuramoto-Sivashinsky Equation (KSE) with Jet Actuations

description: The dataset used in this paper is a collection of snapshots of the Kuramoto-Sivashinsky equation (KSE) experiencing random jet actuations.
DOI: 10.57702/y43wbbg5
title: Cardiac MRI dataset

description: The cardiac dataset is a dataset of MRI images acquired from 100 subjects, with 10 images per subject, using 32 channels and 3T MRI scanner.
DOI: 10.57702/e3wq2zfa
title: Twitter Multimodal Sarcasm Detection Dataset

description: The Twitter multimodal dataset consists of 24k samples of the tweet, image, and image attributes. The dataset is divided into the training set, validation set, and test set in the ratio 80%:10%:10%. The dataset is preprocessed to separate words, emoticons, and hashtags with the NLTK toolkit.
DOI: 10.57702/jjmhry40
title: PASCAL-Part

description: PASCAL-Part is a dataset for semantic part segmentation. It contains images of cars and horses with annotated part segmentation masks.
DOI: 10.57702/k57929ik
title: ImageNet VID

description: Video object detection dataset.
DOI: 10.57702/hw5o93zk
title: Cervical Cancer Segmentation on Multiparametric MRI

description: A dataset of multiparametric MRI images of cervical cancer patients for segmentation and analysis.
DOI: 10.57702/9sv1t0im
title: XCAT phantom

description: The dataset used for training the prior score model for diffusion posterior sampling in CT image reconstruction.
DOI: 10.34740/kaggle/dsv/8724543
title: FLAME 3 -Nadir Thermal Fire Image Dataset
DOI: 10.57702/nrarfsrk
title: Multi-scale 3D Convolution Network for Video Based Person Re-Identiﬁcation

description: Video based person ReID using a two-stream convolution network to explicitly leverage spatial and temporal cues.
DOI: 10.57702/ucs3jrde
title: MARS

description: The video-based person re-identiﬁcation (ReID) aims to identify the given pedestrian video sequence across multiple non-overlapping cameras.
DOI: 10.57702/hruf6id4
title: SFEW

description: The SFEW dataset is a subset of EmotiW2015 in-the-wild emotion dataset.
DOI: 10.57702/u22e5hc4
title: M2Chat: Empowering VLM for Multimodal LLM Interleaved

description: M2Chat is a novel unified multimodal LLM framework for generating interleaved text-image conversation across various scenarios.
DOI: 10.57702/6lutjqji
title: LLaMA-AdapterV2

description: LLaMA-AdapterV2: A parameter-efficient visual instruction model for text-image generation.
DOI: 10.57702/sdwx4iri
title: Kodak24

description: The dataset used in the paper is Kodak24, a dataset for image denoising.
DOI: 10.57702/2uiu6lb8
title: McMaster18

description: The dataset used in the paper for image deblurring tasks.
DOI: 10.57702/wrxz766y
title: Devil in the Number: Towards Robust Multi-modality Data Filter

description: The dataset used in the paper is a web-scale dataset for training a vision-language model. The dataset contains text-image pairs, and the authors propose a novel filter to remove redundant information such as numbers and bracketed content.
DOI: 10.57702/koh3u3fa
title: REDS

description: The proposed StableVSR is built upon a pre-trained Latent Diffusion Model (LDM) for single image super-resolution (SISR). We use Stable Diffusion ×4 Upscaler (SD×4Upscaler)2. It follows the LDM framework [31], which performs the iterative refinement process into a latent space and uses the VAE decoder D [11] to decode latents into RGB images.
DOI: 10.57702/ihb77bzv
title: GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks

description: Font generation experiment using GlyphGAN, including legibility, diversity, and style consistency evaluation.
DOI: 10.57702/09tnix2m
title: Fashion-Mnist

description: A binary imbalanced classification dataset with 28 × 28 grayscale images of 10 classes corresponding to fashion products.
DOI: 10.57702/fychiegs
title: wine, iris, digits, boston, diabete, linnerud

description: The dataset used in this paper is the wine dataset, iris dataset, digits dataset, boston dataset, diabete dataset, and linnerud dataset.
DOI: 10.57702/mdm2qf2v
title: Rosenbrock function, Rastrigin function

description: The dataset used in this paper is the Rosenbrock function and the Rastrigin function.
DOI: 10.57702/osx9njq2
title: Improving Learning Effectiveness For Object Detection and Classiﬁcation in Cluttered Backgrounds

description: The proposed framework generates a training dataset in heterogeneous cluttered backgrounds for object detection and classification.
DOI: 10.57702/uvvkirp6
title: Kvasir-Instrument

description: Kvasir-Instrument dataset consists of 590 annotated frames containing GI procedure tools such as snares, balloons and biopsy forceps, etc.
DOI: 10.57702/vuhz5nmd
title: Multi-Component Image Dataset (MCID)

description: Multi-Component Image Dataset (MCID) is a test dataset containing a set number of components in a single image created by combining multiple images of the ImageNet dataset.
DOI: 10.25952/3hq4-cb92
title: Attachment Anxiety, Self-Ambivalence, Fear of Self, and Obsessive-Compulsive Symptomology

description: Quantitative data file
description: Quantitative data file
DOI: 10.57702/u0uyp8op
title: CIFAR-100 and ImageNet

description: The dataset used in the paper is CIFAR-100 and ImageNet.
DOI: 10.57702/5o7r0muq
title: Aff-Wild2: Extending the Aff-Wild database for affect recognition

description: A multi-task learning framework for emotion recognition and facial image generation
DOI: 10.57702/tnjcccrj
title: Cohn-Kanade database

description: A database for facial expression analysis
DOI: 10.57702/v9m9zxe0
title: SPIn-NeRF

description: The SPIn-NeRF dataset contains 10 scenes, each with 60 training views (with the object to be removed), 40 test views (without the object), and human-annotated object masks per view.
DOI: 10.57702/zty2hpma
title: IBRNet

description: The IBRNet dataset contains 10 scenes, each with 60 training views (with the object to be removed), 40 test views (without the object), and human-annotated object masks per view.
DOI: 10.57702/bupe9mcv
title: LGE-MRI dataset

description: The dataset used for training and testing the U-net architecture for automatic segmentation of LGE-MRI images.
DOI: 10.57702/mzp8y8j5
title: LGE-MRI test dataset

description: The dataset used for testing the U-net architecture for automatic segmentation of LGE-MRI images.
DOI: 10.57702/8ncxtyoq
title: SciTune

description: Human-generated scientific instructions for multimodal instruction tuning
DOI: 10.57702/ebxv02mg
title: ConvNet

description: The dataset used in this paper is a convolutional neural network problem with 60,000 training examples and 10,000 testing examples.
DOI: 10.57702/zx0qbbtk
title: ResNet-18

description: Training neural networks on image datasets generally require extensive experimentation to find the optimal learning rate regime.
DOI: 10.57702/16i2v1na
title: DAVIS

description: The DAVIS dataset is a widely used dataset for video-related tasks, consisting of approximately 2000 frames from 26 human-centric scenarios.
DOI: 10.57702/s92gqlbd
title: NTIRE2019 Real Image Denoising Challenge - Track 2:sRGB

description: The dataset used for training and validation in the NTIRE2019 Real Image Denoising Challenge - Track 2:sRGB.
DOI: 10.57702/nd3btzjs
title: METR-LA dataset

description: The METR-LA dataset contains speed profiles, given in miles per hour (mph), of 207 sensor locations collected from the loop detector on the highways of Los Angeles County.
DOI: 10.57702/ly8zmz1o
title: Spectrum dataset

description: The Spectrum dataset is a synthetic dataset containing spectrum data generated by applying light waves on 4-layer 3D semiconductors and measuring the returning wavelengths.
DOI: 10.57702/cxy6ebx6
title: Exchange-Rate dataset

description: The Exchange-Rate dataset contains daily exchange rates from 8 countries.
DOI: 10.57702/yldyvbas
title: RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation

description: A topological map representation of an environment based on image segments, which are semantically meaningful and open-vocabulary queryable.
DOI: 10.57702/02w2tltv
title: Gibson Env

description: A visual place recognition dataset for embodied agents.
DOI: 10.57702/80wxycnm
title: PanoContext-Living

description: A visual place recognition dataset for embodied agents.
DOI: 10.57702/lgsa8ie1
title: GPCampus-DayLeft

description: A visual place recognition dataset for embodied agents.
DOI: 10.57702/4ox7o97d
title: Mayo-2020

description: The dataset used for training and testing the proposed WIA-LD2ND method.
DOI: 10.57702/1mf0m0md
title: DeepGrowth: A Deep Learning Model for Vestibular Schwannoma Growth Prediction

description: Vestibular schwannoma growth prediction from longitudinal MRI by time-conditioned neural fields
DOI: 10.57702/bl3vt847
title: ConvAI2

description: The ConvAI2 dialogue corpus is a dataset of personalized dialogues with corresponding persona descriptions.
DOI: 10.57702/83uf2554
title: Intracranial Electroencephalography (iEEG) Recordings

description: The dataset used in this study consists of 8 neurosurgical patients who underwent intracranial electroencephalography (iEEG) recordings while listening to speech.
DOI: 10.57702/xnz7djkq
title: Jigsaw Dataset

description: The Jigsaw dataset is a collection of text, where each text is labeled as toxic or non-toxic.
DOI: 10.57702/kqhu0qt8
title: ScanNetv2, ScanNet200, and Replica

description: ScanNetv2, ScanNet200, and Replica datasets for 3D instance segmentation
DOI: 10.57702/7zs78m15
title: Vehicle Color Recognition using Convolutional Neural Network

description: Vehicle color recognition method using convolutional neural network
DOI: 10.57702/2ybb0zke
title: Wearable Data Collection System for Studying Micro-Level E-Scooter Behavior

description: A wearable data collection system for studying micro-level e-Scooter behavior in a naturalistic road environment.
DOI: 10.57702/v72pa2z8
title: Pothole Detection Dataset

description: A dataset of images with pothole annotations from various sources, including Google Earth Pro, AUTOPILOT videos, and GoPro camera images.
DOI: 10.57702/nzhvna0l
title: Lebanese Road Pothole Detection Dataset

description: The dataset used for pothole detection using deep learning
DOI: 10.57702/84qyk3pj
title: FedNST: Federated Noisy Student Training for Automatic Speech Recognition

description: Federated Noisy Student Training for Automatic Speech Recognition
DOI: 10.57702/d3kkbxdy
title: Coded Diffraction Patterns (CDP)

description: The dataset used in the paper is a set of coded diffraction patterns (CDP) with noisy intensity measurements.
DOI: 10.57702/fs5gyhs1
title: Vitiligo (public) dataset

description: The vitiligo (public) dataset contains 672 training, 268 validation, and 401 test images.
DOI: 10.57702/u3e1w35w
title: COCO Detection Dataset

description: The COCO detection dataset is a large-scale object detection benchmark.
DOI: 10.57702/7woynsxz
title: COCO Test-Dev Set

description: The COCO test-dev set is a subset of the COCO detection dataset.
DOI: 10.57702/ycylfuki
title: Synthetic dataset for fabric mechanics estimation

description: A synthetic dataset of depth images of fabrics, with mechanical ground truth parameters, used to train and evaluate a method for estimating fabric mechanics from depth images.
DOI: 10.57702/w1oega6h
title: Real dataset for fabric mechanics estimation

description: A real dataset of depth images of fabrics, with mechanical ground truth parameters, used to test and evaluate a method for estimating fabric mechanics from depth images.
DOI: 10.57702/e8mwpllw
title: NuScenes dataset

description: The dataset used in the paper is the NuScenes dataset, which contains LiDAR point clouds and corresponding semantic annotations.
DOI: 10.57702/gf9iqheu
title: WebCaricature dataset

description: The dataset used in the paper is the WebCaricature dataset, which contains 6,042 caricatures and 5,974 photographs from 252 persons.
DOI: 10.57702/bv52mtqe
title: MISMATCH: Fine-grained Evaluation of Machine-generated Text

description: The dataset used in the paper for fine-grained evaluation of machine-generated text with mismatch error types.
DOI: 10.57702/wtxxlmh1
title: DRIVE and CHASE DB1 datasets

description: Two benchmark datasets for blood vessel segmentation in retinal images
DOI: 10.57702/hnjxo41n
title: M2Former: Multi-Scale Patch Selection for Fine-Grained Visual Recognition

description: Fine-grained visual recognition (FGVR) is a challenging task due to subtle inter-class differences and large intra-class variations.
DOI: 10.57702/3qs03gkd
title: Caltech-UCSD Birds (CUB)

description: Caltech-UCSD Birds (CUB) dataset is a dataset of bird images.
DOI: 10.57702/4pmefdzu
title: NABirds

description: Fine-grained visual classiﬁcation (FGVC) is a challenging computer vision problem, where the task is to au- tomatically recognise objects from subordinate categories.
DOI: 10.57702/xaxxz9v8
title: Single Motion Diffusion Model

description: Single Motion Diffusion Model, a model designed to learn the internal motifs of a single motion sequence with arbitrary topology and synthesize motions of arbitrary length that are faithful to them.
DOI: 10.57702/y2isz8w3
title: Truebones

description: Truebones dataset, a dataset of 3D human motion data.
DOI: 10.57702/xxnm21aw
title: Probe-A

description: This dataset was generated using MSCOCO [22]. The goal is to have high accuracy and confidence in selecting the correct prompt for the respective image where the attribute is swapped.
DOI: 10.57702/f56s2u8e
title: Probe-B

description: This dataset was generated using MSCOCO [22]. The goal is to have high accuracy and confidence in selecting the correct prompt for the respective image where the background is removed.
DOI: 10.57702/mti4vxep
title: GP-Tree: A Gaussian Process Classiﬁer for Few-Shot Incremental Learning

description: Gaussian processes (GPs) are non-parametric, flexible models that work well in many tasks. Combining GPs with deep learning methods via deep kernel learning (DKL) is especially compelling due to the strong representational power induced by the network.
DOI: 10.57702/mdx23ciw
title: Rainfall datasets

description: Rainfall datasets from major cities across the United States
DOI: 10.57702/adfjd03b
title: DreaMo: Articulated 3D Reconstruction From A Single Casual Video

description: A dataset of 42 animal video clips with diverse species and insufficient view coverage from the Internet.
DOI: 10.57702/o4790oyv
title: DukeMTMC-VideoReID

description: The video-based person re-identiﬁcation (ReID) aims to identify the given pedestrian video sequence across multiple non-overlapping cameras.
DOI: 10.57702/exrddo83
title: AG News

description: The dataset used in the paper is a language domain dataset, specifically for sentiment classification, named AG News. The dataset is used to evaluate the performance of Empirical Explainers.
DOI: 10.57702/md0uswrk
title: Metro Passenger Volume Prediction

description: Two real-world metro ridership benchmark datasets, HZMetro and SHMetro, are used to evaluate the performance of our method.
DOI: 10.57702/ytz6rx77
title: Candy, Feathers, Scream, Starry, Mosaic, la Muse, Composition VII, Udnie

description: The dataset is a large-scale synthesized dataset of real and stylized face pairs.
DOI: 10.57702/m7ug9brq
title: CUFSF dataset

description: The dataset is a collection of human face sketches.
DOI: 10.57702/s3uijbkx
title: ML-20M

description: A recommender system generates personalized recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top-K items with high scores.
DOI: 10.57702/zo4g7ixg
title: vKitti2

description: The dataset used in the paper is a synthetic dataset for unsupervised depth estimation, which includes vKitti2, SHIFT, and UrbanSyn datasets.
DOI: 10.57702/u8248r9o
title: SHIFT

description: The dataset used in the paper is a synthetic dataset for unsupervised depth estimation, which includes vKitti2, SHIFT, and UrbanSyn datasets.
DOI: 10.57702/ukt8htxk
title: RSVQAxBEN

description: The RSVQAxBEN dataset is a large-scale benchmark dataset for remote sensing visual question answering, based on the BigEarthNet (BEN) archive and containing 590,326 Sentinel-2 L2A image patches with 12 spectral bands of varying resolution.
DOI: 10.57702/bzkm9sql
title: Extended RSVQAxBEN

description: The extended RSVQAxBEN dataset is an extension of the RSVQAxBEN dataset, including all the spectral bands of Sentinel-2 images with 10m and 20m spatial resolution.
DOI: 10.57702/fbxfqfun
title: U.S. 1950 Census records

description: Two novel datasets—French 19th-century and U.S. 1950 Census records—to demonstrate our approach.
DOI: 10.57702/48kufbtr
title: End-to-End Referring Video Object Segmentation with Multimodal Transformers

description: The referring video object segmentation task (RVOS) involves segmentation of a text-referred object instance in the frames of a given video.
DOI: 10.57702/28wzf42l
title: RefVOS: a closer look at referring expressions for video object segmentation

description: RefVOS: a closer look at referring expressions for video object segmentation.
DOI: 10.57702/4pfmtdfs
title: URVOS: Uniﬁed referring video object segmentation network with a large-scale benchmark

description: URVOS: Uniﬁed referring video object segmentation network with a large-scale benchmark.
DOI: 10.57702/fhbirq85
title: Synthetic diffusion MRI data

description: Synthetic diffusion MRI data generated using Phantomαs
DOI: 10.57702/i7hg8t46
title: Analyzing Social Media to Assess User Satisfaction with Transport for London’s Oyster

description: Social media data for assessing user satisfaction with Transport for London’s Oyster
DOI: 10.57702/nb5q5ea2
title: MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment

description: The proposed method consists of four components: feature extractor using ViT, transposed attention block, scale swin transformer block, and a dual branch structure for patch-weighted quality prediction.