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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Atmosphere

,AiATrack: Attention in?Attention for?Transformer Visual Tracking, AiATrack, by introducing efficient feature reuse and target-background embeddings to make full use of temporal references. Experiments show that our tracker achieves state-of-the-art performance on six tracking benchmarks while running at a real-time speed. Code and models are publicly available at ..

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,Social ODE: Multi-agent Trajectory Forecasting with?Neural Ordinary Differential Equations,e show in extensive experiments that our Social ODE approach compares favorably with state-of-the-art, and more importantly, can successfully avoid sudden obstacles and effectively control the motion of the agent, while previous methods often fail in such cases.

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,Point Cloud Compression with?Range Image-Based Entropy Model for?Autonomous Driving,rforms better in the autonomous driving scene. Experiments on LiDARs with different lines and in different scenarios show that our proposed compression scheme outperforms the state-of-the-art approaches in reconstruction quality and downstream tasks by a wide margin.

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https://doi.org/10.1007/978-3-031-20047-2Computer Science; Informatics; Conference Proceedings; Research; Applications