About Multi-image preprocessing, such as dino, voxelize and 3d vae
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Description
I want to confirm the experimental process.
First, input 150 images into the Dinov2 model to obtain the feature (150, 1024, 37, 37).
Then, by voxelization, project it to the plane and then project it back to the voxel space and then average each voxel, will the feature (1024, 64, 64, 64) be obtained? Will averaging reduce the number of channels(1024)? How to filter the obtained features from 64x64x64=262144 to 20,000?
Finally, the pre-trained model 3D VAE is used to process the feature. What is this pre-trained model? What data is used to pretrain 3D VAE?
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Research direction
Start by locating the repository's multi-image preprocessing, voxelization, and 3D VAE documentation or entry points; the issue names no files or tests. Verify the feature shapes, channel behavior, voxel filtering method, and the 3D VAE's pretraining details, then document confirmed answers and references for each question.
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Assessment
- Tech stack
- machine-learning, python
- Domain
- computer-vision, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100