Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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,MODE: Multi-view Omnidirectional Depth Estimation with?360,?Cameras, maps from different camera pairs via omnidirectional stereo matching and then fuses the depth maps to achieve robustness against mud spots, water drops on camera lenses, and glare caused by intense light. We adopt spherical feature learning to address the distortion of panoramas. In addition, a syn

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moratorium

,Gaussian Activated Neural Radiance Fields for?High Fidelity Reconstruction and Pose Estimation,s require accurate prior camera poses. Although approaches for jointly recovering the radiance field and camera pose exist, they rely on a cumbersome coarse-to-fine auxiliary positional embedding to ensure good performance. We present Gaussian Activated Neural Radiance Fields (GARF), a new positiona

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,Objects Can Move: 3D Change Detection by?Geometric Transformation Consistency,f they undergo rigid motions. A graph cut optimization propagates the changing labels to geometrically consistent regions. Experiments show that our method achieves state-of-the-art performance on the 3RScan dataset against competitive baselines. The source code of our method can be found at ..