datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
OpenMath-Vision-CoT-10kTripVVT-10K
TripVVT-10K Dataset
News
2026.06: TripVVT has been accepted by ECCV 2026.
2026.04: The TripVVT paper is available on arXiv.
The project page is available at https://shaodingbao.github.io/TripVVT/.
TripVVT-10K is a large-scale dataset for in-the-wild Video Virtual Try-On (VVT). It contains 10,031 high-quality video samples with triplet supervision, covering upper-body garments, lower-body garments, and dresses.
TripVVT-10K is released together with the… See the full description on the dataset page: https://huggingface.co/datasets/TripVVT/TripVVT-10K.ArtiMuse-10K
ArtiMuse:
Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
[🌐 Project Page]
[🚀 Online Demo]
[💻 Code]
[📄 Paper]
[[🧩 Checkpoints: 🤗 Hugging Face | 🤖 ModelScope]]
🌟 Building upon on ArtiMuse, we introduce UniPercept, a comprehensive follow-up work that provides a meticulous study on perceptual-level image understanding. It spans Image Aesthetics Assessment (IAA), Image Quality Assessment (IQA), and Image Structure & Texture… See the full description on the dataset page: https://huggingface.co/datasets/Thunderbolt215215/ArtiMuse-10K.S1-Omni-Corpus-10K
S1-Omni-Corpus-10K
An open-source scientific multimodal reasoning dataset subset for S1-Omni
🧬 Model Introduction
S1-Omni is a unified scientific multimodal reasoning model for scientific understanding, prediction, and generation. It is developed by the ScienceOne AI team of the Chinese Academy of Sciences.
S1-Omni addresses fragmented scientific AI capabilities with a shared backbone for cross-disciplinary, cross-modal, and cross-task understanding and reasoning… See the full description on the dataset page: https://huggingface.co/datasets/ScienceOne-AI/S1-Omni-Corpus-10K.SciGenEdit-10K
SciGenEdit-10K
An Open Dataset for Scientific Image Generation and Editing
English | 简体中文
📖 Introduction
SciGenEdit-10K is a public subset released with the S1-Omni-Image project. It is designed for research on scientific image generation, scientific image editing, and multi-turn scientific image generation and editing.
S1-Omni-Image is a unified multimodal model developed by the ScienceOne team at the Chinese Academy of Sciences for scientific… See the full description on the dataset page: https://huggingface.co/datasets/ScienceOne-AI/SciGenEdit-10K.coco2014val_10k
COCO-2014 Val 10K (256×256)
A curated subset of the COCO 2014 Validation set containing 9,986 image-caption pairs, designed as a standard reference benchmark for FID (Fréchet Inception Distance) evaluation in text-to-image generation research.
Dataset Summary
Attribute
Value
Source
COCO 2014 Validation Split
Num Samples
9,986
Resolution
256 × 256 (center-cropped & resized)
Image Format
PNG, RGB
Total Size
~1.2 GB
Random Seed
42
Original Pool
40,504… See the full description on the dataset page: https://huggingface.co/datasets/byliutao/coco2014val_10k.StreetVision-10K
StreetVision-10K
Each sample contains:
A system prompt instructing the model to act as an OSINT/geospatial expert
A user message with a street-level photo and the instruction to determine coordinates
An assistant response with ground-truth coordinates in <direct_lon_lat_output>longitude,latitude</direct_lon_lat_output> format
Format
Each line is a JSON array of ChatML messages:
[
{"role": "system", "content": "..."},
{"role": "user", "content": [… See the full description on the dataset page: https://huggingface.co/datasets/mishl/StreetVision-10K.ArtiMuse-10K
ArtiMuse:
Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
[🌐 Project Page]
[🚀 Online Demo]
[💻 Code]
[📄 Paper]
[[🧩 Checkpoints: 🤗 Hugging Face | 🤖 ModelScope]]
🌟 Building upon on ArtiMuse, we introduce UniPercept, a comprehensive follow-up work that provides a meticulous study on perceptual-level image understanding. It spans Image Aesthetics Assessment (IAA), Image Quality Assessment (IQA), and Image Structure & Texture… See the full description on the dataset page: https://huggingface.co/datasets/to-hope-we-bound/ArtiMuse-10K.bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
bghira/pseudo-camera-10k with responses/captions generated with gemini-2.0-flash-thinking-exp-1219.
The format should be similar to that of liuhaotian/LLaVA-Instruct-150K.
Images can be found in the images.zip folder. The zip also contains .txt captions for ease of use in non-VQA tasks.
Generation Details
If BlockedPromptException, StopCandidateException, or InvalidArgument was returned, the… See the full description on the dataset page: https://huggingface.co/datasets/PJMixers-Images/bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT.smw_10k
Dataset Card for Dataset Name
This data set has been collected By rendering the TAS recorded by drakeeker. This is only the first 10,000 frames for testing only.
Dataset Details
Dataset Description
This data set has 10,000 frames of super mario world rendered from a tool assisted speed run that Was more casual than optimized. I needed 10,000 frames to fine tune a vision language model
Curated by: (ArthurFischel)[https://huggingface.co/ArthurFischel]… See the full description on the dataset page: https://huggingface.co/datasets/ArthurFischel/smw_10k.ArtiMuse-10K
ArtiMuse:
Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
[🌐 Project Page]
[🚀 Online Demo]
[💻 Code]
[📄 Paper]
[[🧩 Checkpoints: 🤗 Hugging Face | 🤖 ModelScope]]
🌟 Building upon on ArtiMuse, we introduce UniPercept, a comprehensive follow-up work that provides a meticulous study on perceptual-level image understanding. It spans Image Aesthetics Assessment (IAA), Image Quality Assessment (IQA), and Image Structure & Texture… See the full description on the dataset page: https://huggingface.co/datasets/gltscc/ArtiMuse-10K.