datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
celebA_spoof
Dataset Card for "celebA_spoof"
More Information needed
sportsmot
SportsMOT
SportsMOT is a large-scale dataset for single-camera multi-object tracking (MOT) in sports videos. It focuses on tracking players in professional sports scenes, where targets exhibit fast and variable-speed motion, frequent occlusion, motion blur, camera motion, and similar team uniforms.
This Hugging Face repository provides SportsMOT in a MOTChallenge-style structure for research, benchmarking, training, and evaluation of multi-object tracking systems in sports… See the full description on the dataset page: https://huggingface.co/datasets/Lekim89/sportsmot.tempface-anti-spoofing-dataset
Face Antispoofing dataset for liveness detection
Anti-Spoofing dataset: live, replay, cut, print, 3D masks - large-scale face anti spoofing
This dataset delivers a single, end-to-end resource for training and benchmarking facial liveness-detection systems. By aggregating live sessions and eleven realistic presentation-attack classes into one collection, it accelerates development toward iBeta Level 1/2 compliance and strengthens model robustness against the full spectrum of spoofing… See the full description on the dataset page: https://huggingface.co/datasets/AxonData/face-anti-spoofing-dataset.sportsd
SportsD: On-Ball Soccer Decision Benchmark
SportsD tests whether a vision-language model picks better on-ball soccer actions than
professional players did, using possession-value (VAEP) ground truth from two World Cups.
Each event freezes a real on-ball moment. The model sees the seconds before the moment
and picks one action: a pass to a specific lettered teammate, or a shot. Every
candidate action has a VAEP expected value, so every answer gets a real value score.
1421… See the full description on the dataset page: https://huggingface.co/datasets/addisonwu05/sportsd.sports-cards
Digital Card Magazine Dataset
This dataset contains sports card images and their associated metadata for training machine learning models in card recognition, text extraction, and value estimation.
Dataset Description
Dataset Summary
A comprehensive collection of sports card images and metadata, including:
Front and back card images
OCR-extracted text with confidence scores
AI-analyzed card attributes
Card details (player, team, year, etc.)
Vision API labels… See the full description on the dataset page: https://huggingface.co/datasets/GotThatData/sports-cards.vlmn_tartandrive100_scand50_coda25_spot100_sub5_full_augmentation_processed_10
Trajectory Ranking Dataset
This dataset contains trajectory ranking results for autonomous navigation scenarios.
Dataset Statistics
Total examples: 39558
Chunks processed: 40
Upload date: 2025-09-13T00:44:30.335177
Features
Image data with terrain analysis
Trajectory rankings and reasoning
Quality and diversity analysis
Terrain and trajectory descriptions
SportsHHI
Dataset Card for SportsHHI
Dataset Summary
SportsHHI is a dataset for video human-human interaction detection. Please refer to SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos for more details. Please refer to this repository for training and evaluation.
Supported Tasks and Leaderboards
Human-Human Interaction Detection
Details about training and evaluation can be found in the GitHub Repository.
Languages
The class labels… See the full description on the dataset page: https://huggingface.co/datasets/MCG-NJU/SportsHHI.2026-06-28T22-03-30plus00-00_gdpvalspot-terrain-dataset
Spot Dataset
FISH_spots
FISH_spots Dataset
The manually verified in situ hybridization fluorescence images and point coordinate dataset.
This dataset contains images and annotations for the task of single-molecule fluorescence in situ hybridization (FISH) spot detection, supporting 2D, 3D, and simulated noisy data. The structure is designed for deep learning model development, training, and evaluation.
Directory Structure
FISH_spots/
├── 2d/
│ ├── csv/
│ ├── image/
│ ├── image_raw/
│ └──… See the full description on the dataset page: https://huggingface.co/datasets/GangCaoLab/FISH_spots.sponsorblock-youtube-metadata-2024
SponsorBlock YouTube Metadata Dataset
A dataset of YouTube video metadata collected from a subset of videos in the SponsorBlock database. This dataset contains metadata, subtitles, engagement heatmaps, live chat, and channel playlist information for popular YouTube videos.
Contains the top videos from the SponsorBlock database that had data added in the year 2024.
Quick Stats
Metric
Value
Total videos
154,536
Videos with subtitles
62,819 (41%)… See the full description on the dataset page: https://huggingface.co/datasets/ScriptSmith/sponsorblock-youtube-metadata-2024.spotify_songsReadme
Dataset Description:
This dataset is brought from kaggle: "30000 Spotify Songs". The dataset contains both numeric and categorical variables describing songs available on Spotify. It includes musical characteristics such as danceability, energy, loudness, valence, tempo, and duration, as well as metadata like artist, album, and genre.
Research Question:
What song characteristics make a track more popular on Spotify?
Target Variable:
The target variable is track_popularity, which… See the full description on the dataset page: https://huggingface.co/datasets/uleeberber/spotify_songs.anti-spoofing-datasetsllava_instruct_mix_jpTranslated using ChatWaifu_12B_v2.2(private)
Prompt
prompt = [
{
'role': 'user',
'content': [
{
'type': 'text',
'text': f"""Translate the sentece to japanese.
If there is any structure like markdown table or chart, using original format.
Here is the sentence to translate: 36.76"""
},
]
},
{
'role': 'assistant',
'content': [
{
'type': 'text',
'text': f"""36.76"""… See the full description on the dataset page: https://huggingface.co/datasets/spow12/llava_instruct_mix_jp.avs-spot
Dataset Card for AVS-Spot Benchmark
This dataset is associated with the paper: "Understanding Co-Speech Gestures in-the-wild"
📝 ArXiv: https://arxiv.org/abs/2503.22668
🌐 Project page: https://www.robots.ox.ac.uk/~vgg/research/jegal
💻 Code: https://github.com/Sindhu-Hegde/jegal
We present JEGAL, a Joint Embedding space for Gestures, Audio and Language. Our semantic gesture representations can be used to perform multiple downstream tasks such as cross-modal retrieval… See the full description on the dataset page: https://huggingface.co/datasets/sindhuhegde/avs-spot.SportR
SportR
SportR is a multi-sport benchmark for rule-infraction reasoning and tactic
recognition across basketball, soccer, American football, badminton, and table
tennis, covering both images (4,789) and video clips (2,052), with a
progressive QA suite and 6,841 human-authored Chain-of-Thought rationales.
⚠️ Access policy. The annotations / QA JSON are open (see the
GitHub repository). The image & video
media in this repository are gated and
released for non-commercial research… See the full description on the dataset page: https://huggingface.co/datasets/haotianxia/SportR.face-anti-spoofing
Face Antispoofing dataset for recognition systems
The dataset consists of 98,000 videos and selfies from 170 countries, providing a foundation for developing robust security systems and facial recognition algorithms.
While the dataset itself doesn't contain spoofing attacks, it's a valuable resource for testing liveness detection system, allowing researchers to simulate attacks and evaluate how effectively their systems can distinguish between real faces and various forms of… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/face-anti-spoofing.vlmn_iphone100_tartandrive100_scand50_coda25_spot100_sub5
vlmn_iphone100_tartandrive100_scand50_coda25_spot100_sub5
Description
VLN Navigation dataset with 100% of iphone data, 100% of tartandrive data, 50% of scand data, 25% of coda data, and 100% of in-domain spot data. Whenever daatsets aren't 100%, they are ranked by curvature and output of length 5.
Processing Parameters
{}
Dataset Configuration
Train dataset:
mixer: mateoguaman/coda_every1_25pct_sub5: 1.0
mateoguaman/iphone_stairs_ramps: 1.0… See the full description on the dataset page: https://huggingface.co/datasets/mateoguaman/vlmn_iphone100_tartandrive100_scand50_coda25_spot100_sub5.celeba-spoof-for-face-antispoofing-testceleba-spoof-dataset
Biometric Attack Dataset
The similar dataset that includes all ethnicities - Anti Spoofing Real Dataset
We suggest you the dataset similar to CelebA Dataset but with photos of real people, additionally the dataset for face anti spoofing and face recognition includes not only images, but videos of the individuals!
The videos were gathered by capturing faces of genuine individuals presenting spoofs, using facial presentations. Our dataset proposes a novel approach that… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/celeba-spoof-dataset.SpokenVisITSpokenVisIT
SpokenVisIT is a real-world visual-speech interaction benchmark built upon VisIT-Bench, designed to evaluate the visual-grounded speech interaction capabilities of omni large multimodal models (LMMs).
Our deepest acknowledgment goes to VisIT-Bench — A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use — which collects a diverse set of real-world visual instructions. SpokenVisIT builds on this foundation by converting the textual instructions into spoken… See the full description on the dataset page: https://huggingface.co/datasets/ICTNLP/SpokenVisIT.Leeds_Sports_PoseSince the official website of this dataset is down, I re-upload the dataset to make it publicly accessible.
If there are any violation of license or personal benefits, please contact me and I will quickly take actions.
The original verison of README file is provided below.
Leeds Sports Pose Dataset
Sam Johnson and Mark Everingham
http://sam.johnson.io/research/lsp.html
This dataset contains 2000 images of mostly sports people
gathered from Flickr. The images have been scaled such that the… See the full description on the dataset page: https://huggingface.co/datasets/LiuRunky/Leeds_Sports_Pose.SpotifyFeatures_sample
Assignment #1 - EDA & Dataset - orian rivlin
Goal:
Explore which audio features are most strongly related to a track’s popularity on Spotify.
This repository includes the dataset sample, a well-documented notebook, saved figures, and a short video walkthrough.
Dataset
Name: Spotify Features (Sample)
File: SpotifyFeatures_sample.csv
Rows: ~10,000 | Columns: 18 (mostly numeric)
Target: popularity (0–100)
Main numeric features: danceability, energy, loudness, speechiness… See the full description on the dataset page: https://huggingface.co/datasets/orianrivlin/SpotifyFeatures_sample.glm-5.3-flash-spotgovdocs1-image
BEE-spoke-data/govdocs1-image
This contains .jpg files from govdocs1. Light deduplication was applied (i.e. jdupes on all files) which removed ~500 duplicate images.
DatasetDict({
train: Dataset({
features: ['image'],
num_rows: 108895
})
})
source
Source info/page: https://digitalcorpora.org/corpora/file-corpora/files/
@inproceedings{garfinkel2009bringing,
title={Bringing Science to Digital Forensics with Standardized Forensic Corpora}… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/govdocs1-image.upvoteweb-posts
upvoteweb: posts
Posts in upvoteweb.
configs
[!IMPORTANT]There are several configs representing different permutations of this dataset. Load the relevant config for the task you are interested in.
Overview of configs:
default: largely unfiltered/unprocessed original data
eduscored: the "eduscore" predicted on the text column with huggingface's trained classifier
en-clean: filter language for en and language_score for > 0.6. Run clean-text on the text col, preserving… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/upvoteweb-posts.Xiang_Wan_BindWeave_KJ_sports_Qwen_Image_4_bind_imagesvlmn_scand_spot_sub5
vlmn_scand_spot_sub5
Description
VLN Navigation dataset with 50% of scand data and 100% of in-domain spot data. Whenever daatsets aren't 100%, they are ranked by curvature and output of length 5.
Processing Parameters
{}
Dataset Configuration
Train dataset:
mixer: mateoguaman/scand_every1_50pct_sub5: 1.0
mateoguaman/spot_every1_sub5: 1.0
split: train
Validation dataset:
mixer: mateoguaman/scand_every1_50pct_sub5: 1.0… See the full description on the dataset page: https://huggingface.co/datasets/mateoguaman/vlmn_scand_spot_sub5.SportFashion_512x512