33 citations · 57 across the 5 of their papers we have counts for
12 papers
Consensus Maximisation Using Influences of Monotone Boolean Functions
Ruwan Tennakoon, David Suter, Erchuan Zhang +2
Consensus maximisation (MaxCon), which is widely used for robust fitting in computer vision, aims to find the largest subset of data that fits the model within some tolerance level…
Unsupervised Learning for Robust Fitting:A Reinforcement Learning Approach
Giang Truong, Huu Le, David Suter +2
Robust model fitting is a core algorithm in a large number of computer vision applications. Solving this problem efficiently for datasets highly contaminated with outliers is, howe…
Quantum Robust Fitting
Tat-Jun Chin, David Suter, Shin-Fang Chng +1
Many computer vision applications need to recover structure from imperfect measurements of the real world. The task is often solved by robustly fitting a geometric model onto noisy…
Monotone Boolean Functions, Feasibility/Infeasibility, LP-type problems and MaxCon
David Suter, Ruwan Tennakoon, Erchuan Zhang +2
This paper outlines connections between Monotone Boolean Functions, LP-Type problems and the Maximum Consensus Problem. The latter refers to a particular type of robust fitting cha…
End-to-end Learning of Object Motion Estimation from Retinal Events for Event-based Object Tracking
Haosheng Chen, David Suter, Qiangqiang Wu +1
Event cameras, which are asynchronous bio-inspired vision sensors, have shown great potential in computer vision and artificial intelligence. However, the application of event came…
Hypergraph Optimization for Multi-structural Geometric Model Fitting
Shuyuan Lin, Guobao Xiao, Yan Yan +2
Recently, some hypergraph-based methods have been proposed to deal with the problem of model fitting in computer vision, mainly due to the superior capability of hypergraph to repr…