datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hot3d
HOT3D-Clips
This Hugging Face repository hosts HOT3D-Clips, a set of curated sub-sequences of the HOT3D dataset.
Download instructions for HOT3D-Clips and the full HOT3D dataset can be found here.
See HOT3D Toolkit for documentation of the data format and for Python utilities (for loading, undistorting fisheye images, rendering using fisheye cameras, etc.).
More details can be found in the HOT3D paper and BOP 2024 report.
lmotudlbop-tudl-rgb-dataset-realbopask-test
BOPASK-Test
Human-verified evaluation benchmark for the BOPASK spatial-reasoning VQA dataset.
Contains 934 question-answer pairs across two testsets:
core — BOPASK-Core: three BOP-Challenge families (HANDAL, HOPE, YCB-V).
lab — BOPASK-Lab : an in-the-wild set of "home / lab" scenes.
Contents at a glance
Split
Family
Records
RGB images
Depth maps
Masks
core
handal
251
43
41
138
core
hope
189
50
29
231
core
ycbv
248
48
48
153
lab
home
246
21
12 (⚠)
52… See the full description on the dataset page: https://huggingface.co/datasets/bhatvineet/bopask-test.tyolicmiruapcbopask-databop-lmo-episodebop-motion-mcq
BOP-Motion-MCQ — multiple-choice motion questions over dense 6-DoF video
Multiple-choice questions about how objects move, derived exactly from dense
6-DoF (object→camera) pose trajectories rather than guessed from pixels. Each row pairs
a short 6fps video clip with one motion MCQ, its per-second motion trajectory, and the
whole-video aggregated answer. The intended task: watch the clip and pick the motion that
actually happens.
Built with the motion-qa pipeline… See the full description on the dataset page: https://huggingface.co/datasets/livctr/bop-motion-mcq.bop-tudl-rgb-dataset-renderbop-lm-episodereal-bop-homebrew-scene-3bop-ycbv-episodesynthetic-bop-homebrew-scene-3-mediumsynthetic-bop-homebrew-scene-3-smallskywalker-drone-bop