datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Tom-and-Jerry-VideoGeneration-Dataset中文阅读
Information
The dataset contains about 6000 scenes sample,
lr: 1E-3 betas: [ 0.8, 0.95 ] eps: 1e-8 weight_decay: 1e-4
After 4000 iterations, all generated content will tend to the target sample
The length of each video is 6 seconds.
The frame rate of the videos is 14 frames per second.
The video resolution is w=540 , h=360.
Dataset Format
.
├── README.md
├── captions.txt
├── videos
└── videos.txt
Used
import os
from datasets import Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Wild-Heart/Tom-and-Jerry-VideoGeneration-Dataset.Disney-VideoGeneration-Dataset
Steamboat Willie - Video Generation Dataset
中文阅读
This dataset contains 69 videos clipped from Disney's Steamboat Willie.
The length of each video is 6 seconds.
The frame rate of the videos is 30 frames per second.
The video resolution is 640 x 380.
All videos are black and white, not in color.
Dataset Format
.
├── README.md
├── metadata.csv
├── prompt.txt
├── videos
└── videos.txt
The prompt.txt file contains descriptions for each video, each description containing… See the full description on the dataset page: https://huggingface.co/datasets/Wild-Heart/Disney-VideoGeneration-Dataset.video-gen-physics-gallery
Paper material (assets/drive)
Two generated galleries plus a figure asset pack. All reproducible from the repo —
don't hand-edit them, re-run the generator.
gallery
what it shows
generator
real_videos/
the input side of the benchmark: real GT episodes, 5 diverse tasks per (embodiment x view-track x markovian/non-markovian) cell
scripts/make_real_video_gallery.py
method_comparison/
the output side: ONE episode rendered by every acceleration method, so a single dir is… See the full description on the dataset page: https://huggingface.co/datasets/doanh25032004/video-gen-physics-gallery.videogenSpotlight-VideoGen-Errors
Spotlight Dataset
Spotlight: Identifying and Localizing Video Generation Errors Using VLMs
Aditya Chinchure, Sahithya Ravi, Pushkar Shukla, Vered Shwartz, Leonid Sigal
🎉 Accepted to ECCV 2026
🌐 Project Page
Summary
Spotlight is a benchmark for evaluating whether Vision Language Models (VLMs) can precisely
localize and explain errors in AI-generated videos. It contains 600 videos generated by
three state-of-the-art Text-to-Video (T2V) models —… See the full description on the dataset page: https://huggingface.co/datasets/UBC-ViL/Spotlight-VideoGen-Errors.video_gen_physicsVideoGen-RewardBench
🏆 [VideoGen-RewardBench Leaderboard]
Introduction
VideoGen-RewardBench is a comprehensive benchmark designed to evaluate the performance of video reward models on modern text-to-video (T2V) systems. Derived from the third-party VideoGen-Eval (Zeng et.al, 2024), we constructing 26.5k (prompt, Video A, Video B) triplets and employing expert annotators to provide pairwise preference labels.
These annotations are based on key evaluation dimensions—Visual Quality (VQ), Motion… See the full description on the dataset page: https://huggingface.co/datasets/KlingTeam/VideoGen-RewardBench.checkpoints
videogenevalkit — checkpoint bundle
All model weights needed by the
videogenevalkit toolkit.
Organized by the benchmark that consumes each set.
Quickstart
hf download videogenevalkit/checkpoints --repo-type dataset --local-dir ckpts
Then the toolkit reads from ckpts/ automatically (path configurable via env vars).
Layout
t2vcompbench/ # T2V-CompBench upstream-mode CV pipeline (6 files, 4.6 GB)
groundingdino_swint_ogc.pth # GD-SwinT-OGC… See the full description on the dataset page: https://huggingface.co/datasets/videogenevalkit/checkpoints.video_gen_physics_datasetvideo_gen_physics_real_videoMotion-X-Videoazm-archive-20260909-videogenreward
videogenreward.tar
Backup of an existing dataset archive, preserving its original bytes.
File: videogenreward.tar
Size: 13,441,536,000 bytes
SHA256: b909864ad8f71353665430e961210373bd34b1bc4acd7a52d5149a4b16546e71
Verify the downloaded archive with sha256sum -c SHA256SUMS.
videogen-rewardbench-qingyingvideogen-rewardbench-easyanimatev4videogen-rewardbench-viduvideogen-rewardbench-opensora1-2videogen-rewardbench-tongyismoke-data
videogenevalkit — smoke-data (canonical layout)
A ~5 GB cross-benchmark slice ready to run end-to-end with
videogenevalkit.
Each subdir is already in the layout the toolkit's eval command expects.
Quickstart
hf download videogenevalkit/smoke-data --repo-type dataset --local-dir data/smoke
# One eval per benchmark — all use the same shape:
videvalkit eval --bench worldjen --videos data/smoke/worldjen/videos --prompts-file data/smoke/worldjen/prompts.jsonl… See the full description on the dataset page: https://huggingface.co/datasets/videogenevalkit/smoke-data.VIDEOGENVideo_Generationvideogen-rewardbench-gen3video_genvideogen-rewardbench-lumavideogen-rewardbench-minimaxVideoGenBias-Data
VideoGenBias Data
This Hugging Face Dataset repository stores the real generated videos and paper data tables for the VideoGenBias project. The companion analysis code is intended to live in the GitHub repository VideoGenBias.
Dataset repository: https://huggingface.co/datasets/XiaoranFace/VideoGenBias-Data
Layout
data/videos/<model>/<category>/<language>/prompt_<NN>/video_<II>.mp4
data/metadata/video_index.csv
data/metadata/video_checksums.csv… See the full description on the dataset page: https://huggingface.co/datasets/Tsinghua-AIoT/VideoGenBias-Data.videogen-rewardbench-cogvideoxvideogen-rewardbench-klingVideoGen_Evalvideo-generator-ai-agent
Video Generator Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP
This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well as the monthly updated Web performance metrics, including Google,Bing average search ranking positions, Github Stars, Arxiv References, etc.
The dataset is helpful for AI… See the full description on the dataset page: https://huggingface.co/datasets/DeepNLP/video-generator-ai-agent.videogenerationdataset1