Abstract: 2D-3D joint learning is essential and effective for fundamental 3D vision tasks, such as 3D semantic segmentation, due to the complementary information these two visual modalities contain.

Abstract: Supervised methods on 3D medical image segmentation need large amounts of annotated data, but annotating is time-consuming. Also, existing 3D segmentation methods capture more global ...

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A robust and efficient C++ physics engine for 2D/3D simulations, featuring collision detection, rigid body dynamics, and soft-body physics. Designed for easy integration into game engines and ...

TL;DR: Our paper presents a new and effective end-to-end lifting framework that achieves state-of-the-art (SOTA) performance for 3D Gaussian segmentation, without the need for pre-processing (e.g., ...

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