3d-asset
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All datasets matching “3d-asset”3D_LLM_Diffusion-trimodal-assets-v11
3D LLM Diffusion: Tri-Modal Assets v11
This dataset repository contains the large data artifacts required to reproduce
the v11 text/XRD/crystal routing layer and train the released Qwen latent
adapter. It accompanies
Yangfan78/3D_LLM_Diffusion-trimodal-qwen-v11.
Contents
Path
Contents
embeddings/trimodal_cond_emb_v11/
final v11 train/validation/benchmark latent tables
corpus/mm_corpus/
27,136 train and 9,047 validation text records plus alignment… See the full description on the dataset page: https://huggingface.co/datasets/Yangfan78/3D_LLM_Diffusion-trimodal-assets-v11.LabHorizon-3D-Asset-Perception
LabHorizon 3D Asset Perception
Pushing the Limits of Laboratory 3D Perception and Long-Horizon Planning via Protocol-Aligned Action Prediction
Overview | News | Highlights | Dataset | Evaluation | Leaderboard | Training | Citation
🔎 Overview
This dataset is the Level 1 split of LabHorizon. Each example pairs three rendered views of the same laboratory asset with historical experimental actions and a set of… See the full description on the dataset page: https://huggingface.co/datasets/Backup-SU-CongLab/LabHorizon-3D-Asset-Perception.MESHY.AI_800_GLB_3D-Assets_Categorised_and_Labelled
MESHY_GLB.zip - 809 Samples GLB/GLTF (Textured, Categorised).
MESHY_PLY.zip - 788 Samples PLY (Vertex Colored, Uncategorised).
This dataset is also available in vertex color projected PLY files with an open source model browser that makes the task of creating hand-picked subsets of this dataset fast and easy, you can download it here at: https://archive.org/details/meshy-collection-1.7z
I curated this selection from assets generated by members of the MESHY.AI Discord server.
I mostly… See the full description on the dataset page: https://huggingface.co/datasets/tfnn/MESHY.AI_800_GLB_3D-Assets_Categorised_and_Labelled.3D-Reconstruction-Benchmark-Asset-Inspection
Asset Inspection Dataset
This dataset's scenes are arranged as follows:
scene/
├── cam_parameters.tar
├── depths.tar
├── images.tar
├── scene.glb Scene
└── scene.blend
The office building scene has four surface soiling settings, so it is arranged as follows
office_building
├── cam_parameters.tar
├── depths.tar
├── high_soiling_images.tar
├── low_soiling_images.tar
├── medium_soiling_images.tar
├── office_building.glb
├── very_low_soiling_images.tar
└── Office_model.blend… See the full description on the dataset page: https://huggingface.co/datasets/Slighting3121/3D-Reconstruction-Benchmark-Asset-Inspection.3d-demo-assets3DAsset