5 citations · 5 across the 2 of their papers we have counts for
4 papers
Active-Passive SimStereo -- Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods
Laurent Jospin, Allen Antony, Lian Xu +3
In stereo vision, self-similar or bland regions can make it difficult to match patches between two images. Active stereo-based methods mitigate this problem by projecting a pseudo-…
Bayesian Learning for Disparity Map Refinement for Semi-Dense Active Stereo Vision
Laurent Valentin Jospin, Hamid Laga, Farid Boussaid +1
A major focus of recent developments in stereo vision has been on how to obtain accurate dense disparity maps in passive stereo vision. Active vision systems enable more accurate e…
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation
Hamid Laga, Laurent Valentin Jospin, Farid Boussaid +1
Estimating depth from RGB images is a long-standing ill-posed problem, which has been explored for decades by the computer vision, graphics, and machine learning communities. Among…
Embedded polarizing filters to separate diffuse and specular reflection
Laurent Valentin Jospin, Gilles Baechler, Adam Scholefield
Polarizing filters provide a powerful way to separate diffuse and specular reflection; however, traditional methods rely on several captures and require proper alignment of the fil…