Camera shake leads to non-uniform image blurs. Stateof-the-art methods for removing camera shake model the blur as a linear combination of homographically transformed versions of ...
Michael Hirsch, Christian Schuler, Stefan Harmelin...
Non-blind deconvolution is a key component in image deblurring systems. Previous deconvolution methods assume a linear blur model where the blurred image is generated by a linear ...
In this paper, we propose a long-term motion model for visual object tracking. In crowded street scenes, persistent occlusions are a frequent challenge for tracking algorithm and ...
Haifeng Gong, Jack Sim, Maxim Likhachev, Jianbo Sh...
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
We describe a directed bilinear model that learns higherorder groupings among features of natural images. The model represents images in terms of two sets of latent variables: one...
Jack Culpepper, Jascha Sohl-Dickstein, Bruno Olaha...
We propose a visual recognition system that is designed for fine-grained visual categorization. The system is composed of a machine and a human user. The user, who is unable to c...
Catherine Wah, Steven Branson, Pietro Perona, Serg...
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Rank correlation measures are known for their resilience to perturbations in numeric values and are widely used in many evaluation metrics. Such ordinal measures have rarely been ...
Jay Yagnik, Dennis Strelow, David Ross, Ruei-sung ...
We address the problem of reconstructing 3D face models from large unstructured photo collections, e.g., obtained by Google image search or from personal photo collections in iPho...