srutisrinidhi/3DModelSearch
3DModelSearch — Renders & Embeddings Precomputed data for 3DModelSearch: multi-view image renders, turntable videos, and LanguageBind embeddings for 3D models, used in Learning Visual and Motion Aware 3D Model Representations for Semantic Retriev. These let you reproduce retrieval results without re-rendering or re-embedding. Contents File Size Contents embeddings.tar.gz ~ GB out/Embeddings/<uid>_image.pt, <uid>_video.pt, and out/models_data.csv… See the full description on the dataset page: https://huggingface.co/datasets/srutisrinidhi/3DModelSearch.
3DModelSearch — Renders & Embeddings
Precomputed data for 3DModelSearch: multi-view image renders, turntable videos, and LanguageBind embeddings for 3D models, used in Learning Visual and Motion Aware 3D Model Representations for Semantic Retriev. These let you reproduce retrieval results without re-rendering or re-embedding.
Contents
- Image embeddings:
[6, 768]tensors (6 views, LanguageBind image encoder). - Video embeddings:
[768]tensors (LanguageBind video encoder). models_data.csvmaps eachuidto its render + embedding paths (paths are relative to the code repo root).
Source .glb models are not included — fetch them from Objaverse as described in the code repo.
Usage
pip install huggingface_hub
huggingface-cli download <HF_USER>/<REPO> embeddings.tar.gz --repo-type dataset --local-dir .
tar -xzf embeddings.tar.gz # -> out/
tar -xzf videos.tar.gz # -> data/Videos/
tar -xzf images.tar.gz # -> data/Images/
