111 citations · 151 across the 6 of their papers we have counts for
6 papers
Seeing What Is Not There: Learning Context to Determine Where Objects Are Missing
Jin Sun, David W. Jacobs
Most of computer vision focuses on what is in an image. We propose to train a standalone object-centric context representation to perform the opposite task: seeing what is not ther…
A New Rank Constraint on Multi-view Fundamental Matrices, and its Application to Camera Location Recovery
Soumyadip Sengupta, Tal Amir, Meirav Galun +4
Accurate estimation of camera matrices is an important step in structure from motion algorithms. In this paper we introduce a novel rank constraint on collections of fundamental ma…
Solving Uncalibrated Photometric Stereo Using Fewer Images by Jointly Optimizing Low-rank Matrix Completion and Integrability
Soumyadip Sengupta, Hao Zhou, Walter Forkel +3
We introduce a new, integrated approach to uncalibrated photometric stereo. We perform 3D reconstruction of Lambertian objects using multiple images produced by unknown, directiona…
Riemannian Metric Learning for Symmetric Positive Definite Matrices
Raviteja Vemulapalli, David W. Jacobs
Over the past few years, symmetric positive definite (SPD) matrices have been receiving considerable attention from computer vision community. Though various distance measures have…
Locally Scale-Invariant Convolutional Neural Networks
Angjoo Kanazawa, Abhishek Sharma, David Jacobs
Convolutional Neural Networks (ConvNets) have shown excellent results on many visual classification tasks. With the exception of ImageNet, these datasets are carefully crafted such…
Comparing apples to apples in the evaluation of binary coding methods
Mohammad Rastegari, Shobeir Fakhraei, Jonghyun Choi +2
We discuss methodological issues related to the evaluation of unsupervised binary code construction methods for nearest neighbor search. These issues have been widely ignored in li…