datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.ECCV_Event_Video_Depth_Estimation
Event-Guided Video Depth Estimation Workshop Dataset
This dataset is a mirrored and aligned workshop-ready version of the DVD event-guided video depth estimation data.
It packages each scene into a canonical folder tree that aligns:
low-light RGB frames
per-frame event slices
a scene-level lowlight_event.npz
the matched depth ground truth copied from inference_results/*/normal/depth.npz
The dataset is designed for direct upload to Hugging Face as a dataset repository.
The official… See the full description on the dataset page: https://huggingface.co/datasets/Ethanliang99/ECCV_Event_Video_Depth_Estimation.AerialMetric-ECCV2026
AerialMetric-ECCV2026
This repository is the main dataset hub for the paper AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World.
It includes more than 65k aerial image-depth pairs, and all depth maps are metric.
Project homepage: https://kuieless.github.io/AerialMetric-ECCV2026-page/
Repository: https://github.com/kuieless/AerialMetric-ECCV2026
It contains the training data, test data, and the moge2-aerial weights used by the… See the full description on the dataset page: https://huggingface.co/datasets/Kuiee/AerialMetric-ECCV2026.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.MedVidU_ECCV2026_TrainVal
ECCV 2026 Workshop on Medical Video Understanding (MedVidU @ ECCV 2026) — Train / Val Split
This is the public train / val split for the MedVidU Challenge at the ECCV 2026 Workshop on Medical Video Understanding. This split is derived from the benchmark introduced in MedGRPO: Multi-Task Reinforcement Learning for Heterogeneous Medical Video Understanding (CVPR 2026).
Participants are free to use this split for any combination of training and local validation.
Final challenge… See the full description on the dataset page: https://huggingface.co/datasets/UII-AI/MedVidU_ECCV2026_TrainVal.ECCV26-ARAvid_motion_mag_eccv18AerialMetric-ECCV2026
AerialMetric-ECCV2026
This repository is the main dataset hub for the paper AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World.
It includes more than 65k aerial image-depth pairs, and all depth maps are metric.
Project homepage: https://kuieless.github.io/AerialMetric-ECCV2026-page/
Repository: https://github.com/kuieless/AerialMetric-ECCV2026
It contains the training data, test data, and the moge2-aerial weights used by the… See the full description on the dataset page: https://huggingface.co/datasets/Addy0811/AerialMetric-ECCV2026.LAM_Cases_For_ECCVSUP-NeRF-ECCV2024
SUP-NeRF: A Streamlined Unification of Pose Estimation and NeRF for Monocular 3D Object Reconstruction
Project Website | Paper | Talk
Yuliang Guo, Abhinav Kumar, Cheng Zhao, Ruoyu Wang, Xinyu Huang, Liu RenBosch Research North America, Bosch Center for AI
in ECCV 2024
This dataset includes the additional instance masks computed from maskrcnn and 3D object detection results from FCOS3D on nuScenes, KITTI, and Waymo (front-vew) datasets.
license: mit