Detect 3D object from one image using features from 3D-aware diffusion with 3DiffTection
Detect 3D object from one image using features from 3D-aware diffusion with 3DiffTection
3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features
arXiv paper abstract https://arxiv.org/abs/2311.04391
arXiv PDF paper https://arxiv.org/pdf/2311.04391.pdf
... present 3DiffTection, a state-of-the-art method for 3D object detection from single images, leveraging features from a 3D-aware diffusion model.
... image diffusion models ... are not optimized for 3D tasks, and often exhibit a domain gap when applied to the target data.
... bridges these gaps through two ... tuning strategies: geometric and semantic. For geometric ... fine-tune a diffusion model to perform novel view synthesis conditioned on a single image, by introducing a novel epipolar warp operator.
... For semantic refinement, ... further train the model on target data with detection supervision. Both tuning phases employ ControlNet to preserve the integrity of the original feature capabilities.
... conduct a test-time prediction ensemble across multiple virtual viewpoints ... obtain 3D-aware features that are tailored for 3D detection and excel in identifying cross-view point correspondences.
... model emerges as a powerful 3D detector, substantially surpassing previous benchmarks ...
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