This chapter opens with a review of how well Meta’s Segment Anything Model (SAM) has been doing.
It was a huge hit and changed the game in 2D image segmentation entirely.
The next step is to extend this success to include 3D segmentation.
SA3D leverages advancements in NeRF and the SAM model to create a new kind of 3D modeling that can easily be adapted to any pre-trained NeRF model without requiring any changes or re-training, making it highly compatible and adaptable.
There have been some attempts to extend NeRF-based techniques for 3D segmentation.
The segmentation maps generated by SAM are then projected onto 3D mask grids using density-guided inverse rendering, providing initial 3D forecast results.
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