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DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion
(Center for Brains, Minds and Machines (CBMM), 2018-06-19)
In this paper, we study the task of detecting semantic parts of an object, e.g., a wheel of a car, under partial occlusion. We propose that all models should be trained without seeing occlusions while being able to transfer ...
Semantic Part Segmentation using Compositional Model combining Shape and Appearance
(Center for Brains, Minds and Machines (CBMM), arXiv, 2015-06-08)
In this paper, we study the problem of semantic part segmentation for animals. This is more challenging than standard object detection, object segmentation and pose estimation tasks because semantic parts of animals often ...
Detecting Semantic Parts on Partially Occluded Objects
(Center for Brains, Minds and Machines (CBMM), 2017-09-04)
In this paper, we address the task of detecting semantic parts on partially occluded objects. We consider a scenario where the model is trained using non-occluded images but tested on occluded images. The motivation is ...
Visual concepts and compositional voting
(Center for Brains, Minds and Machines (CBMM), 2018-03-27)
It is very attractive to formulate vision in terms of pattern theory , where patterns are defined hierarchically by compositions of elementary building blocks. But applying pattern theory to real world images is very ...