This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
We propose a method that detects and segments multiple, partially occluded objects in images. A part hierarchy is defined for the object class. Whole-object segmentor and part de...
We present a shape-based algorithm for detecting and
recognizing non-rigid objects from natural images. The existing
literature in this domain often cannot model the objects
ver...
Xiang Bai, Xinggang Wang, Longin Jan Latecki, Weny...
In this paper, we present a learning procedure called probabilistic boosting network (PBN) for joint real-time object detection and pose estimation. Grounded on the law of total p...
Jingdan Zhang, Shaohua Kevin Zhou, Leonard McMilla...
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...