datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
HRVQAHRScene
HRScene - High Resolution Image Understanding
🌐 Homepage |
🤗 Dataset |
📖 arXiv |
GitHub
⭐ About HRScene
We introduce HRScene, a novel unified benchmark for HRI understanding with rich scenes. HRScene incorporates 25 real-world datasets and 2 synthetic diagnostic datasets with resolutions ranging from 1,024 × 1,024 to 35,503 × 26,627. HRScene is collected and re-annotated by 10 graduate-level annotators, covering 25 scenarios, ranging from microscopic and radiology… See the full description on the dataset page: https://huggingface.co/datasets/Wenliang04/HRScene.vidore_v3_hrViDoRe V3 : HR
This dataset, HR, is a corpus of reports released by the european union, intended for complex-document understanding tasks. It is one of the 10 corpora comprising the ViDoRe v3 Benchmark.
About ViDoRe v3
ViDoRe V3 is our latest benchmark for RAG evaluation on visually-rich documents from real-world applications. It features 10 datasets with, in total, 26,000 pages and 3099 queries, translated into 6 languages. Each query comes with human-verified relevant pages… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_hr.HRVideoBench
HRVideoBench
This repo contains the test data for HRVideoBench, which is released under the paper "VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation". VISTA is a video spatiotemporal augmentation method that generates long-duration and high-resolution video instruction-following data to enhance the video understanding capabilities of video LMMs.
🌐 Homepage | 📖 arXiv | 💻 GitHub | 🤗 VISTA-400K | 🤗 Models | 🤗 HRVideoBench… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/HRVideoBench.HRSID
HRSID: High-Resolution SAR Images Dataset (Ship Detection)
Unofficial redistribution of the HRSID high-resolution SAR ship-detection dataset, reformatted into a standardized YOLO-compatible directory layout. License status is unclear -- see License before using this beyond research.
Disclaimer
This repository is not an official release of HRSID.
HRSID was created by Shunjun Wei, Xiangfeng Zeng, Qizhe Qu, Mou Wang, Hao Su, and Jun Shi and released via… See the full description on the dataset page: https://huggingface.co/datasets/dronefreak/HRSID.cvsearch_hr8kVisualizations of CVSearch
Citation
@misc{li2026cvsearchempoweringmultimodalllms,
title={CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception},
author={Liupeng Li and Haoqian Kang and Zhenyu Lu and Jinpeng Wang and Bin Chen and Ke Chen and Yaowei Wang},
year={2026},
eprint={2605.23655},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.23655},
}… See the full description on the dataset page: https://huggingface.co/datasets/tothanhdat/cvsearch_hr8k.vidore_v3_hr_mteb_format
Vidore3HrRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
Retrieve associated pages according to questions.
Task category
t2i
Domains
Academic
Reference
https://huggingface.co/blog/QuentinJG/introducing-vidore-v3
Source datasets:
vidore/vidore_v3_hr
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("Vidore3HrRetrieval")
evaluator = mteb.MTEB([task])… See the full description on the dataset page: https://huggingface.co/datasets/vidore/vidore_v3_hr_mteb_format.HR-MMSearch
Dataset Description
HR-MMSearch is a benchmark designed to evaluate the Agentic Reasoning and Search capabilities of Multimodal Large Language Models in complex visual tasks.
This dataset was introduced by SenseTime Research in the paper SenseNova-MARS: Empowering Multimodal Agentic Reasoning and Search via Reinforcement Learning.
Key Features:
High-Resolution Images: Contains high-resolution image inputs, requiring the model to possess fine-grained visual perception… See the full description on the dataset page: https://huggingface.co/datasets/sensenova/HR-MMSearch.RSVQA-HR_qwen_finetuningRSVQA-HR-2kA 2k subset of the validation split of the RSVQA HR dataset ported to HF for ease-of-use in quick remote sensing VQA evaluation.
For more information and attribution please refer to the original dataset: https://rsvqa.sylvainlobry.com/#dataset
uavid-3d-scenes
UAVid-3D-Scenes
UAVid-3D-Scenes is a depth-estimation centric extension for the UAVid semantic dataset, organizing the original sequences based on the larger scenes they were captured in, providing undistorted RGB frames paired with metric depth maps obtained through COLMAP reconstructions and scaling.
📃 This dataset accompanies the paper TanDepth: Leveraging Global DEMs for Metric Monocular Depth Estimation in UAVs
License: CC BY-NC-SA 4.0 Creative Commons… See the full description on the dataset page: https://huggingface.co/datasets/hrflr/uavid-3d-scenes.DIV2K_train_HRgsr-hrv-stress-detection-dataset
GSR + HRV Stress Detection — Cleaned Volunteer Dataset
Cleaned, anonymized physiological recordings from 124 volunteers used to train the GSR+HRV stress detection model. Collected as part of an applied research project at Almutlaq United Company.
Full data-cleaning pipeline and training code: github.com/Alansi775/GSR-COSSINUS_VOLUNTEERS_DATA_FOR_ML
Protocol
Each volunteer completed an identical 4-phase session, recorded at 1 Hz:
Stage
Duration
Purpose… See the full description on the dataset page: https://huggingface.co/datasets/malansi/gsr-hrv-stress-detection-dataset.kovidore-v2-hr-beirKoViDoRe v2 : HR
This dataset, HR, is a corpus of reports on workforce outlook and employment policy in korea, intended for complex-document understanding tasks. It is one of the 4 corpora comprising the KoViDoRe v2 Benchmark.
Links
Github: https://github.com/whybe-choi/kovidore-benchmark
Collection: https://huggingface.co/collections/whybe-choi/kovidore-benchmark-beir-v2
Data Generation Pipeline: https://github.com/whybe-choi/kovidore-data-generator
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/whybe-choi/kovidore-v2-hr-beir.HRBench4KHRF-high-resolution-fundusarXiv:2501.18921https://arxiv.org/abs/2501.18921
improved_aesthetics_4.5plus-ultra-hrversion https://git-lfs.github.com/spec/v1
oid sha256:98b45ea81164d1e1a1dd82255207053b15cd6c69d922a1c5cf3387ce604d4b74
size 28
HRVQA-2kA 2k subset of the validation split of the HRVQA dataset ported to HF for ease-of-use in quick remote sensing VQA evaluation.
For more information and attribution please refer to the original dataset: https://hrvqa.nl/
HRBench8Kmtm24-akkadian-v3HRSOD
HRSOD (High-Resolution Salient Object Detection)
High-resolution salient object detection dataset, mirrored to the nobg org for convenience. Each example is a full-resolution RGB image paired with a binary saliency ground-truth mask.
image: RGB source image
mask: binary saliency ground-truth mask (single channel)
Splits: train (HRSOD-TR) and test (HRSOD-TE).
Source & credit
Originally released with "Towards High-Resolution Salient Object Detection" (Zeng et al.… See the full description on the dataset page: https://huggingface.co/datasets/nobg/HRSOD.adaptive-dice-maestro-dataset-mergedhr-bench-8k-800kovidore-v2-hr-mteb
KoVidore2HrRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
Retrieve associated pages according to questions. This dataset, HR, is a corpus of reports on workforce outlook and employment policy in korea, intended for complex-document understanding tasks.
Task categoryt2i
Domains
Social
Reference
https://github.com/whybe-choi/kovidore-data-generator
Source datasets:
whybe-choi/kovidore-v2-hr-beir
How to evaluate on this task
You can evaluate… See the full description on the dataset page: https://huggingface.co/datasets/whybe-choi/kovidore-v2-hr-mteb.HRLS-dataset
HRLS-Datasets
This dataset card aims to describe the datasets used in the FTSD-SegNet.
Install
pip install huggingface-hub
Usage
# Step 1: Download datasets
huggingface-cli download --repo-type dataset Face901/HRLS-dataset --local-dir data --include hrls.zip
# Step 2: Extract datasets
unzip hrls.zip -d hrls
HRP4K
HRP4K: High-Resolution Road Pothole Detection Dataset
Unofficial redistribution of the HRP4K road pothole-detection dataset (V1.00, Zenodo), under the original CC BY 4.0 license, with a documented upstream train-split completeness gap.
Disclaimer
This repository is not an official release of the HRP4K dataset.
HRP4K was created by Hanshen Chen, Zhoulin Tu, Yu Zhao, and Jianfeng Ye, who retain all copyright and intellectual property rights (to the… See the full description on the dataset page: https://huggingface.co/datasets/dronefreak/HRP4K.HR-VITON
Dataset Card for "HR-VITON"
More Information needed
NOAA-HRRR-CONUS-ImageCaptionFlickr2K_HR_PCA_interp_file_nozoom_psfs_SYNTH_invarhrbench_4k_cross_400