3 papers
cs.LG2022
Efficient Maximal Coding Rate Reduction by Variational Forms
Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan +3
The principle of Maximal Coding Rate Reduction (MCR) has recently been proposed as a training objective for learning discriminative low-dimensional structures intrinsic to high…
cs.CV2021
Boosting RANSAC via Dual Principal Component Pursuit
Yunchen Yang, Xinyue Zhang, Tianjiao Ding +3
In this paper, we revisit the problem of local optimization in RANSAC. Once a so-far-the-best model has been found, we refine it via Dual Principal Component Pursuit (DPCP), a robu…
cs.CV2020
Learning to Parse Wireframes in Images of Man-Made Environments
Kun Huang, Yifan Wang, Zihan Zhou +3
In this paper, we propose a learning-based approach to the task of automatically extracting a "wireframe" representation for images of cluttered man-made environments. The wirefram…