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

地殼

,BEVFormer: Learning Bird’s-Eye-View Representation from?Multi-camera Images via?Spatiotemporal Tran this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal

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,Domain Adaptive Hand Keypoint and?Pixel Localization in?the?Wild,we only have labeled images taken under very different conditions (.., indoors). In the real world, it is important that the model trained for both tasks works under various imaging conditions. However, their variation covered by existing labeled hand datasets is limited. Thus, it is necessary to ad