We propose a graph-based semi-supervised symmetric matching framework that performs dense matching between two uncalibrated wide-baseline images by exploiting the results of sparse...
Jianxiong Xiao, Jingni Chen, Dit-Yan Yeung, Long Q...
Abstract. This paper presents a theory that encompasses both "plenoptic" (microlens based) and "heterodyning" (mask based) cameras in a single frequency-domain ...
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
Computer vision has traditionally focused on extracting structure, such as depth, from images acquired using thin-lens or pinhole optics. The development of computational imaging i...
Object detection and pixel-wise scene labeling have both been active research areas in recent years and impressive results have been reported for both tasks separately. The integra...