Most of the current machine learning approaches to IR---including search and recommendation tasks---are mostly designed based on the basic idea of matching, which work from the perceptual and similarity learning perspective. This include both the ...

Recent years have witnessed the success of machine learning and especially deep learning in many research areas such as Vision and Language Processing, Information Retrieval and Recommender Systems, Social Networks and Conversational Agents. Though ...

We present a method for estimating articulated human pose from a single static image based on a graphical model with novel pairwise relations that make adaptive use of local image measurements. More precisely, we specify a graphical model for human pose ...

Detecting objects becomes difficult when we need to deal with large shape deformation, occlusion and low resolution. We propose a novel approach to i) handle large deformations and partial occlusions in animals (as examples of highly deformable objects), ...

In this paper we study the role of context in existing state-of-the-art detection and segmentation approaches. Towards this goal, we label every pixel of PASCAL VOC 2010 detection challenge with a semantic category. We believe this data will provide ...