activity
20182021
most citedOnline Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data

4 citations · 4 across the 1 of their papers we have counts for

collaborators

5 papers

cs.LG20214 cited

Online Continual Learning with Natural Distribution Shifts: An Empirical Study with Visual Data

Zhipeng Cai, Ozan Sener, Vladlen Koltun

Continual learning is the problem of learning and retaining knowledge through time over multiple tasks and environments. Research has primarily focused on the incremental classific…

cs.CV2019

Consensus Maximization Tree Search Revisited

Zhipeng Cai, Tat-Jun Chin, Vladlen Koltun

Consensus maximization is widely used for robust fitting in computer vision. However, solving it exactly, i.e., finding the globally optimal solution, is intractable. A* tree searc…

cs.CV2018

Practical optimal registration of terrestrial LiDAR scan pairs

Zhipeng Cai, Tat-Jun Chin, Alvaro Parra Bustos +1

Point cloud registration is a fundamental problem in 3D scanning. In this paper, we address the frequent special case of registering terrestrial LiDAR scans (or, more generally, le…

cs.CV2018

Deterministic consensus maximization with biconvex programming

Zhipeng Cai, Tat-Jun Chin, Huu Le +1

Consensus maximization is one of the most widely used robust fitting paradigms in computer vision, and the development of algorithms for consensus maximization is an active researc…

cs.CV2018

Robust Fitting in Computer Vision: Easy or Hard?

Tat-Jun Chin, Zhipeng Cai, Frank Neumann

Robust model fitting plays a vital role in computer vision, and research into algorithms for robust fitting continues to be active. Arguably the most popular paradigm for robust fi…