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Found 3 papers, 0 papers with code
Motion From Structure (MfS): Searching for 3D Objects in Cluttered Point Trajectories
Object detection has been a long standing problem in computer vision, and state-of-the-art approaches rely on the use of sophisticated features and/or classifiers.
Feature and Region Selection for Visual Learning
There are four main benefits of our approach: (1) Our approach accommodates non-linear additive kernels such as the popular $\chi^2$ and intersection kernel; (2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; (3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; (4) we point out strong connections with multiple kernel learning and multiple instance learning approaches.
Piecewise Planar and Compact Floorplan Reconstruction from Images
The second challenge is the need of a sophisti- cated regularization technique that enforces piecewise pla- narity, to suppress clutter and yield high quality texture mapped models.
