4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 1 cited
RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation
Chang Nie, Guangming Wang, Zhe Liu +3
Robust estimation is a crucial and still challenging task, which involves estimating model parameters in noisy environments. Although conventional sampling consensus-based algorith…
cs.CV2023★ 4 cited
AffineGlue: Joint Matching and Robust Estimation
Daniel Barath, Dmytro Mishkin, Luca Cavalli +3
We propose AffineGlue, a method for joint two-view feature matching and robust estimation that reduces the combinatorial complexity of the problem by employing single-point minimal…
cs.CV2023★ 2 cited
Consensus-Adaptive RANSAC
Luca Cavalli, Daniel Barath, Marc Pollefeys +1
RANSAC and its variants are widely used for robust estimation, however, they commonly follow a greedy approach to finding the highest scoring model while ignoring other model hypot…