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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,Emotion Recognition for Multiple Context Awareness,certainty in expressing emotions and fail to model multiple context representations complementarily. To alleviate these issues, we present a context-aware emotion recognition framework that combines four complementary contexts. The first context is multimodal emotion recognition based on facial expr

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,Localizing Visual Sounds the Easy Way,ining. Previous works often seek high audio-visual similarities for likely positive (sounding) regions and low similarities for likely negative regions. However, accurately distinguishing between sounding and non-sounding regions is challenging without manual annotations. In this work, we propose a

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,Learning Visual Styles from Audio-Visual Associations,nt a method for learning visual styles from unlabeled audio-visual data. Our model learns to manipulate the texture of a scene to match a sound, a problem we term .. Given a dataset of paired audio-visual data, we learn to modify input images such that, after manipulation, they are more likely to co

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,Remote Respiration Monitoring of Moving Person Using Radio Signals,rious remote applications (e.g., telehealth or emergency detection). The existing nRRM approaches mainly analyze fine details from videos to extract minute respiration signals; however, they have practical limitations in that the head or body of a subject must be quasi-stationary. In this study, we

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,: A Dataset for Physical Audiovisual CommonSense Reasoning,the physical world. Fundamental to this reasoning is .: understanding the physical properties and affordances of available objects, how they can be manipulated, and how they interact with other objects. Physical commonsense reasoning is fundamentally a multi-sensory task, since physical properties a

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