datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cmevs-erp-eval
CM-EVS: A Coverage-Curated Panoramic RGB-D Dataset for Indoor Scene Understanding
CM-EVS is a curated panoramic RGB-D dataset built under a single principle: maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible. The release is structured as one redistributable Blender indoor data archive plus four license-aware adapter packages that regenerate matched frames locally from upstream sources whose terms forbid redistribution.
v1.0… See the full description on the dataset page: https://huggingface.co/datasets/anon-cmevs-2026/cmevs-erp-eval.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
Dataset rendering and preparation code (only .step files are required): https://github.com/DavidXu-JJ/eccv2026-cad-challenge-data-render
This repository contains the public… See the full description on the dataset page: https://huggingface.co/datasets/jingwei-xu-00/eccv2026-cad-challenge-data.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
This repository contains the public data package for the challenge. The
evaluation Space accepts STEP predictions for the private evaluation split and
updates the leaderboard… See the full description on the dataset page: https://huggingface.co/datasets/Qiao123rvvr/eccv2026-cad-challenge-data.ridgelora-cross-sensor-sd302d-f-to-m-20260825
RidgeLoRA-FP: SD302A-F to SD302D-M cross-sensor experiment
This public archive contains the leakage-controlled direct cross-sensor
experiment used to evaluate whether Stage-2 synthetic target-sensor images
help recognition on a physically different real sensor.
Locked protocol
Source/condition sensor: NIST SD302A device F.
Target sensor: NIST SD302D device M.
Identity: subject:finger-position; the same fingers exist across both
collections.
Subject split: 160… See the full description on the dataset page: https://huggingface.co/datasets/LamTNguyen/ridgelora-cross-sensor-sd302d-f-to-m-20260825.mer2026-features
MER2026 Track 1 — Quickstart Guide
Hướng dẫn từng bước để chạy training và tạo file submission cho MER-Cross (Track 1) sử dụng pre-extracted features tại HuggingFace: hhieupt/mer2026-features.
Mục lục
Mô tả bài toán và dữ liệu
Yêu cầu hệ thống
Clone repo ban tổ chức
Cài đặt môi trường
Tải dữ liệu từ HuggingFace
Giải nén và tổ chức thư mục
Tạo file config.py
Training
Tạo file submission
Lưu ý và mẹo
1. Mô tả bài toán và dữ liệu
Bài… See the full description on the dataset page: https://huggingface.co/datasets/hhieupt/mer2026-features.tgk-ai-image-generators-2026
We Tested 10 AI Image Generators on Faces, Text and Ads
Most AI image-generator comparisons reduce the models to a score. We wanted to see the mistakes.
These Guys Know gave ten current models the same three practical briefs in August 2026: a close-up face, exact medical text inside a photographed hospital monitor, and a luxury fragrance advertisement where the person, bottle, label and location needed to look believable together.
We kept the first valid output for every… See the full description on the dataset page: https://huggingface.co/datasets/These-Guys-Know/tgk-ai-image-generators-2026.15-09-2026google-ads-benchmark-2026
Note on checksums. This README.md carries the YAML dataset-card header required by the Hugging Face hub, so its SHA-256 differs from the entry in checksums.txt; that entry refers to the canonical README in the GitHub mirror. All data files are byte-identical across mirrors. Load any table with load_dataset("ivitskiy/google-ads-benchmark-2026", "<config_name>").
Ivitskiy Ads Lab: Google Ads Panel & Benchmark Compilation 2026 (Open Research Dataset)
Two things in one package.… See the full description on the dataset page: https://huggingface.co/datasets/ivitskiy/google-ads-benchmark-2026.ysda-2026-seminar-yatasks-api