cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.f4b6e5
title: Occurrence Download

description: A dataset containing 2934 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Country is Colombia",
 {
 "or" : [
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "Geometry POLYGON((-75.65263 6.35684,-75.6901 6.2231,-75.57769 6.15198,-75.51127 6.14859,-75.44825 6.19939,-75.40567 6.25865,-75.45506 6.31283,-75.65263 6.35684))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cerdocyon C.E.H.Smith, 1839"
 ]
}

 The dataset includes 2934 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0232861-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/cczz4cf
title: CCDC 922695: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cczz4dg
title: CCDC 922696: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cczz49c
title: CCDC 922693: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cczz4bd
title: CCDC 922694: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cczz48b
title: CCDC 922692: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cczz479
title: CCDC 922691: Experimental Crystal Structure Determination

description: Related Article: Tarlok S. Lobana, Poonam Kumari, Alfonso Castineiras, Ray J. Butcher|2013|Eur.J.Inorg.Chem.|2013|3557|doi:10.1002/ejic.201300209
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21979/n9/5g18b1
title: WildAvatar: Learning In-the-wild 3D Avatars from the Web

description: Existing research on avatar creation is typically limited to laboratory datasets, which require high costs against scalability and exhibit insufficient representation of the real world. On the other hand, the web abounds with off-the-shelf real-world human videos, but these videos vary in quality and require accurate annotations for avatar creation. To this end, we propose an automatic annotating pipeline with filtering protocols to curate these humans from the web. Our pipeline surpasses state-of-the-art methods on the EMDB benchmark, and the filtering protocols boost verification metrics on web videos. We then curate WildAvatar, a web-scale in-the-wild human avatar creation dataset extracted from YouTube, with 10,000+ different human subjects and scenes. WildAvatar is at least 10x richer than previous datasets for 3D human avatar creation and closer to the real world. To explore its potential, we demonstrate the quality and generalizability of avatar creation methods on WildAvatar. We will publicly release our code, data source links and annotations to push forward 3D human avatar creation and other related fields for real-world applications.
DOI: 10.7910/dvn/b7in6l
title: Food Security Simulator – Papua New Guinea

description: The Food Security Simulator Papua New Guinea (FSS-PNG) is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks, along with changes in preferences, on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.
description: EXCEL, 2016
description: Country Level
description: This tool will only function properly if both Excel files are downloaded together, removed from the zip folder, and are saved in the same, new folder.
DOI: 10.21979/n9/q57zyr
title: TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion

description: Radar-Camera depth estimation aims to predict dense and accurate metric depth by fusing input images and Radar data. Model efficiency is crucial for this task in pursuit of real-time processing on autonomous vehicles and robotic platforms. However, due to the sparsity of Radar returns, the prevailing methods adopt multi-stage frameworks with intermediate quasi-dense depth, which are time-consuming and not robust. To address these challenges, we propose TacoDepth, an efficient and accurate Radar-Camera depth estimation model with one-stage fusion. Specifically, the graph-based Radar structure extractor and the pyramid-based Radar fusion module are designed to capture and integrate the graph structures of Radar point clouds, delivering superior model efficiency and robustness without relying on the intermediate depth results. Moreover, TacoDepth can be flexible for different inference modes, providing a better balance of speed and accuracy. Extensive experiments are conducted to demonstrate the efficacy of our method. Compared with the previous state-of-the-art approach, TacoDepth improves depth accuracy and processing speed by 12.8% and 91.8%. Our work provides a new perspective on efficient Radar-Camera depth estimation.
DOI: 10.21979/n9/bjphcp
title: MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers

description: Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this potential is largely unrealized because these assets always need to be converted to meshes for 3D industry applications, and the meshes produced by current mesh extraction methods are significantly inferior to Artist-Created Meshes (AMs), i.e., meshes created by human artists. Specifically, current mesh extraction methods rely on dense faces and ignore geometric features, leading to inefficiencies, complicated post-processing, and lower representation quality. To address these issues, we introduce MeshAnything, a model that treats mesh extraction as a generation problem, producing AMs aligned with specified shapes. By converting 3D assets in any 3D representation into AMs, MeshAnything can be integrated with various 3D asset production methods, thereby enhancing their application across the 3D industry. The architecture of MeshAnything comprises a VQ-VAE and a shape-conditioned decoder-only transformer. We first learn a mesh vocabulary using the VQ-VAE, then train the shape-conditioned decoder-only transformer on this vocabulary for shape-conditioned autoregressive mesh generation. Our extensive experiments show that our method generates AMs with hundreds of times fewer faces, significantly improving storage, rendering, and simulation efficiencies, while achieving precision comparable to previous methods.
DOI: 10.7910/dvn/ns1a7v
title: Food Security Simulator – Kenya

description: The Food Security Simulator Kenya (FSS-KEN) is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks, along with changes in preferences, on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.
description: Country Level
description: EXCEL, 2016
description: This tool will only function properly if both Excel files are downloaded together, removed from the zip folder, and are saved in the same, new folder.
DOI: 10.21979/n9/ok5ssq
title: SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE

description: Autoregressive models have demonstrated remarkable success across various fields, from large language models (LLMs) to large multimodal models (LMMs) and 2D content generation, moving closer to artificial general intelligence (AGI). Despite these advances, applying autoregressive approaches to 3D object generation and understanding remains largely unexplored. This paper introduces Scale AutoRegressive 3D (SAR3D), a novel framework that leverages a multi-scale 3D vector-quantized variational autoencoder (VQVAE) to tokenize 3D objects for efficient autoregressive generation and detailed understanding. By predicting the next scale in a multi-scale latent representation instead of the next single token, SAR3D reduces generation time significantly, achieving fast 3D object generation in just 0.82 seconds on an A6000 GPU. Additionally, given the tokens enriched with hierarchical 3D-aware information, we finetune a pretrained LLM on them, enabling multimodal comprehension of 3D content. Our experiments show that SAR3D surpasses current 3D generation methods in both speed and quality and allows LLMs to interpret and caption 3D models comprehensively.
DOI: 10.7910/dvn/wwmn6h
title: Food Security Simulator – Nigeria

description: The Food Security Simulator Nigeria (FSS-NGA) is an innovative and easy-to-use, MS-Excel-based tool for assessing the potential short-term impacts of food price or household income shocks, along with changes in preferences, on food security and people’s diets. The Simulator is an ideal tool for first-cut forward-looking evaluations of direct, household-level outcomes of economic crises and policy responses in a timely manner. The tool allows users to enter positive and negative price or income changes in percentage terms and provides simulated changes for a diverse set of food-consumption- and diet-quality-related indicators. In addition to detailed tabular presentations of all simulation results by household income quintile and residential area, key indicator results are summarized in concise overview tables and visualized in graphs for easy export and use in reports. The underlying data include estimates from representative household survey data and rigorous, sophisticated food demand models to capture consumer behavior.
description: EXCEL, 2016
description: Country Level
description: This tool will only function properly if both Excel files are downloaded together, removed from the zip folder, and are saved in the same, new folder.
DOI: 10.6084/m9.figshare.30325450
title: Energy Transition City Data

description: Resource-depleted city
DOI: 10.6084/m9.figshare.30325450.v1
title: Energy Transition City Data

description: Resource-depleted city
DOI: 10.6084/m9.figshare.30325456.v2
title: Michael Okpara University of Agricultural Umudike (MOUAU) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: Michael Okpara University of Agricultural Umudike (MOUAU) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department
DOI: 10.6084/m9.figshare.30325456.v3
title: Modibbo Adama University of Technology (MAUTECH) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: Modibbo Adama University of Technology (MAUTECH) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department
DOI: 10.21979/n9/ff4yjy
title: Text4Seg: Reimagining Image Segmentation as Text Generation

description: Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks; however, effectively integrating image segmentation into these models remains a significant challenge. In this paper, we introduce Text4Seg, a novel text-as-mask paradigm that casts image segmentation as a text generation problem, eliminating the need for additional decoders and significantly simplifying the segmentation process. Our key innovation is semantic descriptors, a new textual representation of segmentation masks where each image patch is mapped to its corresponding text label. This unified representation allows seamless integration into the auto-regressive training pipeline of MLLMs for easier optimization. We demonstrate that representing an image with 16×16 semantic descriptors yields competitive segmentation performance. To enhance efficiency, we introduce the Row-wise Run-Length Encoding (R-RLE), which compresses redundant text sequences, reducing the length of semantic descriptors by 74% and accelerating inference by 3×, without compromising performance. Extensive experiments across various vision tasks, such as referring expression segmentation and comprehension, show that Text4Seg achieves state-of-the-art performance on multiple datasets by fine-tuning different MLLM backbones. Our approach provides an efficient, scalable solution for vision-centric tasks within the MLLM framework.
DOI: 10.6084/m9.figshare.30325456.v4
title: National Open University of Nigeria (NOUN) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: National Open University of Nigeria (NOUN) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department
DOI: 10.21979/n9/3dcdxv
title: SFDM: Robust Decomposition of Geometry and Reflectance for Realistic Face Rendering from Sparse-view Images

description: In this study, we introduce a novel two-stage technique for decomposing and reconstructing facial features from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual. To synthesize 3D facial models more realistically, we endeavor to decouple key facial attributes from the RGB color, including geometry, diffuse reflectance, and specular reflectance. Specifically, we design a Sparse-view Face Decomposition Model (SFDM): 1) In the first stage, we create a general facial template from a wide array of individual faces, encapsulating essential geometric and reflectance characteristics. 2) Guided by this template, we refine a specific facial model for each individual in the second stage, considering the interaction between geometry and reflectance, as well as the effects of subsurface scattering on the skin. With these advances, our method can reconstruct high-quality facial representations from as few as three images. The comprehensive evaluation and comparison reveal that our approach outperforms existing methods by effectively disentangling geometric and reflectance components, significantly enhancing the quality of synthesized novel views, and paving the way for applications in facial relighting and reflectance editing.
DOI: 10.6084/m9.figshare.30325456.v5
title: Nigerian Defence Academy (NDA) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: Nigerian Defence Academy (NDA) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department
DOI: 10.6084/m9.figshare.30325456.v6
title: Nnamdi Azikiwe University (UNIZIK) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: Nnamdi Azikiwe University (UNIZIK) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department
DOI: 10.21979/n9/vx5wah
title: Disco4D: Disentangled 4D Human Generation and Animation from a Single Image

description: We present Disco4D, a novel Gaussian Splatting framework for 4D human generation and animation from a single image. Different from existing methods, Disco4D distinctively disentangles clothings (with Gaussian models) from the human body (with SMPL-X model), significantly enhancing the generation details and flexibility. It has the following technical innovations. 1) Disco4D learns to efficiently fit the clothing Gaussians over the SMPL-X Gaussians. 2) It adopts diffusion models to enhance the 3D generation process, e.g., modeling occluded parts not visible in the input image. 3) It learns an identity encoding for each clothing Gaussian to facilitate the separation and extraction of clothing assets. Furthermore, Disco4D naturally supports 4D human animation with vivid dynamics. Extensive experiments demonstrate the superiority of Disco4D on 4D human generation and animation tasks.
DOI: 10.6084/m9.figshare.30325456.v7
title: Obafemi Awolowo University (OAU) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department

description: Obafemi Awolowo University (OAU) 2025/2026 Diploma Form/Pre Degree Form Call on 07076040542 to apply and For Admission Process on how to be admitted and mode of payment of School Fee And Acceptance Fee Contact school Admin Department +2347076040542 now to apply and for mode of making school fees, Tutions, any for more information +2347076040542. This is direct from the admin department