Browsing CBMM Memo Series by Author "Zhang, Zhishuai"

Now showing items 1-4 of 4

    • DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion 

      Zhang, Zhishuai; Xie, Cihang; Wang, Jianyu; Xie, Lingxi; Yuille, Alan L. (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 ...

    • Detecting Semantic Parts on Partially Occluded Objects 

      Wang, Jianyu; Xe, Cihang; Zhang, Zhishuai; Zhu, Jun; Xie, Lingxi; e.a. (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 ...

    • Single-Shot Object Detection with Enriched Semantics 

      Zhang, Zhishuai; Qiao, Siyuan; Xie, Cihang; Shen, Wei; Wang, Bo; e.a. (Center for Brains, Minds and Machines (CBMM), 2018-06-19)
      We propose a novel single shot object detection network named Detection with Enriched Semantics (DES). Our motivation is to enrich the semantics of object detection features within a typical deep detector, by a semantic ...

    • Visual concepts and compositional voting 

      Wang, Jianyu; Zhang, Zhishuai; Xie, Cihang; Zhou, Yuyin; Premachandran, Vittal; e.a. (Center for Brains, Minds and Machines (CBMM), 2018-03-27)
      It is very attractive to formulate vision in terms of pattern theory [26], where patterns are defined hierarchically by compositions of elementary building blocks. But applying pattern theory to real world images is very ...