1 citations · 2 across the 5 of their papers we have counts for
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GRVS: a Generalizable and Recurrent Approach to Monocular Dynamic View Synthesis
Thomas Tanay, Mohammed Brahimi, Michal Nazarczuk +5
Synthesizing novel views from monocular videos of dynamic scenes remains a challenging problem. Scene-specific methods that optimize 4D representations with explicit motion priors…
Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo
Mohammed Brahimi, Bjoern Haefner, Zhenzhang Ye +2
Neural approaches have shown a significant progress on camera-based reconstruction. But they require either a fairly dense sampling of the viewing sphere, or pre-training on an exi…
Exploring Regions of Interest: Visualizing Histological Image Classification for Breast Cancer using Deep Learning
Imane Nedjar, Mohammed Brahimi, Said Mahmoudi +2
Computer aided detection and diagnosis systems based on deep learning have shown promising performance in breast cancer detection. However, there are cases where the obtained resul…
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering
Mohammed Brahimi, Bjoern Haefner, Tarun Yenamandra +2
We propose an end-to-end inverse rendering pipeline called SupeRVol that allows us to recover 3D shape and material parameters from a set of color images in a super-resolution mann…
On the well-posedness of uncalibrated photometric stereo under general lighting
Mohammed Brahimi, Yvain Quéau, Bjoern Haefner +1
Uncalibrated photometric stereo aims at estimating the 3D-shape of a surface, given a set of images captured from the same viewing angle, but under unknown, varying illumination. W…
Deep interpretable architecture for plant diseases classification
Mohammed Brahimi, Said Mahmoudi, Kamel Boukhalfa +1
Recently, many works have been inspired by the success of deep learning in computer vision for plant diseases classification. Unfortunately, these end-to-end deep classifiers lack…