datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
GSD-Sensitivity-Taxonomy-Labels
GSD-Sensitivity Taxonomy: Task Labels for Remote Sensing VQA
Per-task D / M1 / M2 taxonomy labels, inter-annotator agreement (IAA) data, and
evaluation traces for four public RS-VQA benchmarks.
Companion to *G. Park and D.-H. Lee, "Identifying the Measurement Gap in Remote
Sensing VQA with a GSD-Sensitive Taxonomy," IEEE Geosci. Remote Sens. Lett., 2026*
— accepted, DOI to follow. Code: github.com/ganghyunnnn/GSD-Sensitivity-Taxonomy
⚠️ This dataset contains annotations and… See the full description on the dataset page: https://huggingface.co/datasets/ganghyunnnn/GSD-Sensitivity-Taxonomy-Labels.fashion-recommendation-images
High-Resolution Fashion Product Images
This dataset is a highly optimized, high-resolution subset of the popular Fashion Product Images Dataset originally hosted on Kaggle.
It contains thousands of unique e-commerce fashion products, combining high-resolution product images with multiple descriptive label attributes.
All low-resolution thumbnails and anomalies have been aggressively filtered out. Every image in this dataset has a minimum resolution of 640px on its shortest… See the full description on the dataset page: https://huggingface.co/datasets/GangHitman/fashion-recommendation-images.PRLx-GAN-synthetic-rim
PRLx-GAN
Repository for Synthetic Generation and Latent Projection Denoising of Rim Lesions in Multiple Sclerosis published in Synthetic Data at CVPR 2025.
Summary
Paramagnetic rim lesions (PRLs) are a rare but highly prognostic lesion subtype in multiple sclerosis, visible only on susceptibility ($\chi$) contrasts. This work presents a generative framework to:
Synthesize new rim lesion maps that address class imbalance in training data
Enable a novel denoising… See the full description on the dataset page: https://huggingface.co/datasets/agr78/PRLx-GAN-synthetic-rim.deepscan-dataset
Tropical Reef Fish Dataset
A dataset of tropical reef fish images for species-level image classification, with additional negative classes for out-of-distribution rejection.
Dataset Description
Images were scraped from iNaturalist using research-grade observations with CC0 or CC-BY licenses. The dataset covers 12 species across 9 families, targeting fish commonly encountered by snorkelers at depths of 0–10 meters in tropical reef environments.
Two negative classes are… See the full description on the dataset page: https://huggingface.co/datasets/fish-gang/deepscan-dataset.