datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mixlora-eval-data
🚀 MixLoRA Evaluation Data
This dataset is the held-out multimodal evaluation suite used in
Multimodal Instruction Tuning with Conditional Mixture of LoRA (ACL 2024).
It bundles 9 instruction-formatted tasks (mm_tasks/) plus the MME benchmark
(mme/) used to evaluate MixLoRA and baseline models in the paper.
The 9 tasks in mm_tasks/ are the zero-shot / held-out task split from
Vision-Flan. MME is a
separate benchmark, evaluated independently.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/yingss/mixlora-eval-data.MMS-VPR
MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments
Overview
MMS-VPR is the first large-scale multimodal street-level visual place recognition dataset featuring comprehensive integration of images, videos, and rich textual annotations with day–night coverage and a 7-year temporal span in dense pedestrian-only environments.
MMS-VPR comprises 110,529 images and 2,527 video clips… See the full description on the dataset page: https://huggingface.co/datasets/Yiwei-Ou/MMS-VPR.Urban-ImageNet
🏙️ Urban-ImageNet
A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception from Social Media Imagery.
Urban-ImageNet fills a critical gap between computer vision and urban studies by treating cities not simply as visual scenes, but as lived, socially produced, and experientially activated spaces.
Overview
ImageNet taught models to recognise objects. Urban-ImageNet teaches them to understand how people experience cities.… See the full description on the dataset page: https://huggingface.co/datasets/Yiwei-Ou/Urban-ImageNet.UnsafeBench
Dataset Card for Dataset Name
[Update]: we added the caption/prompt information (if there is one) in case other researchers need it. It is not used in our study though.
The dataset consists of 10K safe/unsafe images of 11 different types of unsafe content and two sources (real-world VS AI-generated).
Dataset Details
Source
# Safe
# Unsafe
# All
LAION-5B (real-world)
3,228
1,832
5,060
Lexica (AI-generated)
2,870
2,216
5,086
All
6,098
4,048
10,146… See the full description on the dataset page: https://huggingface.co/datasets/yiting/UnsafeBench.CHUBS
CHUBS: A Large-Scale Dataset of Chu Bamboo Slip Script
Code | Paper (upcoming)
Introduction
This is a large-scale dataset of Chu bamboo slip (CBS, Chinese: 楚简, chujian) script, an ancient Chinese script used during the Spring and Autumn period over 2,000 years ago. This dataset consists of two parts:
The main dataset where each example is an image and the corresponding text label. This part is contained in the glyphs.zip ZIP file.
A character detection dataset… See the full description on the dataset page: https://huggingface.co/datasets/chen-yingfa/CHUBS.metacloak_celeba_vggface2
Dataset Card for MetaCloak
Dataset Summary
This repository provides datasets from the MetaCloak.
For each dataset, *-gen is the subset used for protecting, and *-eval is used as a clean reference to calculate some quality metrics.
from datasets import load_dataset
dataset = load_dataset("yixin/metacloak_celeba_vggface2")
Contact
Contact Us: yixinliucs@gmail.com
pascal-voc
Pascal VOC
Dataset Summary
The Pascal Visual Object Classes (VOC) dataset is a widely used benchmark in the field of computer vision. It is designed for object detection, image classification, semantic segmentation, and action classification tasks. The dataset provides a comprehensive set of annotated images covering 20 object classes, allowing researchers to evaluate and compare the performance of various algorithms.
Note: This dataset repository contains all editions of… See the full description on the dataset page: https://huggingface.co/datasets/yizhangdev/pascal-voc.AIGUARD_dataset
🔥 (ACL2025) AIGUARD: A Benchmark and Lightweight Detection of E-commerce AIGC Risks 🔥
The statistic of the dataset are shown in the table below.
Category
Total
Positive
Negative
Ratio
Abnormal Body
76,800
12,768
64,032
1:5
Violating Physical Laws
90,880
15,154
75,726
1:5
Misleading or Illogical Context
65,280
10,847
54,433
1:5
Harmful or Problematic Message
20,460
5,116
15,344
1:3
🔨 Dataset Description
AIGUARD, the first comprehensive AIGC bad… See the full description on the dataset page: https://huggingface.co/datasets/yinyueguilai/AIGUARD_dataset.mnist
Dataset Card for MNIST
Dataset Summary
The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class.
Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/Yizhao666/mnist.yid_synth_pangolineINFO: I'm not giving access to users with 0 models/0 datasets/0 activity - sharing is both ways
Dataset Summary
The Yiddish Synthetic Pangoline Dataset is a comprehensive collection of synthetic Yiddish document images generated using a custom implementation of Pangoline, a text-to-image synthesis tool. The dataset contains high-quality synthetic Yiddish text rendered as images, along with corresponding ground truth text and ALTO-XML layout annotations. This dataset is designed… See the full description on the dataset page: https://huggingface.co/datasets/johnlockejrr/yid_synth_pangoline.UnsafeConcepts
Dataset Card for Dataset Name
The dataset consists of 1.5K unsafe images associated with 75 unsafe concepts, covering 9 categories.
Uses
from datasets import load_dataset
dataset = load_dataset("yiting/UnsafeConcepts")["train"]
print(dataset[0])
{'image': <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=512x512 at 0x14C0BEC12730>,
'category': 'Hate',
'unsafe_concept': 'Swastika'}
Out-of-Scope Use
This dataset is intended for research purposes only.… See the full description on the dataset page: https://huggingface.co/datasets/yiting/UnsafeConcepts.