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Article
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose
Recognition of human poses and actions is crucial for autonomous systems to interact smoothly with people. However, cameras generally capture human poses in 2D as images and videos, which can have significant ...
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Chapter and Conference Paper
View-Invariant Probabilistic Embedding for Human Pose
Depictions of similar human body configurations can vary with changing viewpoints. Using only 2D information, we would like to enable vision algorithms to recognize similarity in human body poses across multip...
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Chapter and Conference Paper
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Spatial pyramid pooling module or encode-decoder structure are used in deep neural networks for semantic segmentation task. The former networks are able to encode multi-scale contextual information by probing ...
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Chapter and Conference Paper
Visual Recognition with Humans in the Loop
We present an interactive, hybrid human-computer method for object classification. The method applies to classes of objects that are recognizable by people with appropriate expertise (e.g., animal species or airp...