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20182022
most citedA Survey on Deep Learning Architectures for Image-based Depth Reconstruction

25 citations · 31 across the 7 of their papers we have counts for

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cs.CV2022

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…

cs.CV2021

Learnable Triangulation for Deep Learning-based 3D Reconstruction of Objects of Arbitrary Topology from Single RGB Images

Tarek Ben Charrada, Hedi Tabia, Aladine Chetouani +1

We propose a novel deep reinforcement learning-based approach for 3D object reconstruction from monocular images. Prior works that use mesh representations are template based. Thus…

cs.CV2021

A Survey of Deep Learning Techniques for Weed Detection from Images

A S M Mahmudul Hasan, Ferdous Sohel, Dean Diepeveen +2

The rapid advances in Deep Learning (DL) techniques have enabled rapid detection, localisation, and recognition of objects from images or videos. DL techniques are now being used i…

cs.CV2020

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…

cs.CV20191 cited

RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques

Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun

Object detection from RGB images is a long-standing problem in image processing and computer vision. It has applications in various domains including robotics, surveillance, human-…

cs.CV201925 cited

A Survey on Deep Learning Architectures for Image-based Depth Reconstruction

Hamid Laga

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. In th…