A new open-source project, WiFi DensePose, uses ordinary WiFi signals to detect human movement behind walls without cameras.
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🔍 Rethinking Unified Models: We identify two critical limitations in existing unified multi-person eyeblink detection models: (1) feature granularity conflict between face localization and eyeblink ...
Abstract: Face occlusion often makes it challenging to detect facial landmarks and head pose accurately. In this work, we present a pipeline to estimate facial landmarks and head pose when only a ...
Abstract: Computer vision advancements allow motion transfer for animating static objects in images. However, current methods rely on manually collected motion labels and struggle with accurate shape ...
The BBox-Mask-Pose (BMP) method integrates detection, pose estimation, and segmentation into a self-improving loop by conditioning these tasks on each other. This approach enhances all three tasks ...