Today, visual recognition systems are still rarely employed in robotics applications. Perhaps one of the main reasons for this is the lack of demanding benchmarks that mimic such ...
We propose a method of clustering images that combines algorithmic and human input. An algorithm provides us with pairwise image similarities. We then actively obtain selected, mo...
We introduce a framework for defining a distance on the (non-Euclidean) space of Linear Dynamical Systems (LDSs). The proposed distance is induced by the action of the group of o...
We introduce a saliency model based on two key ideas. The first one is considering local and global image patch rarities as two complementary processes. The second one is based o...
In this paper we examine the effect of receptive field designs on classification accuracy in the commonly adopted pipeline of image classification. While existing algorithms us...
We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noi...
We present a novel framework for multiple object tracking in which the problems of object detection and data association are expressed by a single objective function. The framewor...
Zheng Wu, Ashwin Thangali, Stan Sclaroff, Margrit ...
In this paper, we address a practical problem of crossscenario clothing retrieval - given a daily human photo captured in general environment, e.g., on street, finding similar cl...
Si Liu, Zheng Song, Guangcan Liu, Changsheng Xu, H...
In this paper, we address the problem of video object segmentation, which is to automatically identify the primary object and segment the object out in every frame. We propose a n...
Co-segmentation is defined as jointly partitioning multiple images depicting the same or similar object, into foreground and background. Our method consists of a multiplescale mu...