4 citations · 16 across the 20 of their papers we have counts for
5 papers · 1 filter
Seeing Through Smoke: Surgical Desmoking for Improved Visual Perception
Jingpei Lu, Fengyi Jiang, Xiaorui Zhang +2
Minimally invasive and robot-assisted surgery relies heavily on endoscopic imaging, yet surgical smoke produced by electrocautery and vessel-sealing instruments can severely degrad…
UNet-AF: Alias-free UNet architectures
Jérémy Scanvic, Quentin Barthélemy, Julián Tachella
The simplicity and effectiveness of UNet architectures make them ubiquitous in image restoration, segmentation, and diffusion models. They are often assumed to be equivariant to tr…
Efficient Unrolled Networks for Large-Scale 3D Inverse Problems
Romain Vo, Julián Tachella
Deep learning-based methods have revolutionized the field of imaging inverse problems, yielding state-of-the-art performance across various imaging domains. The best performing net…
Equivariant Splitting: Self-supervised learning from incomplete data
Victor Sechaud, Jérémy Scanvic, Quentin Barthélemy +2
Self-supervised learning for inverse problems allows to train a reconstruction network from noise and/or incomplete data alone. These methods have the potential of enabling learnin…
Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks
Jérémy Scanvic, Quentin Barthélemy, Julián Tachella
The design of convolutional neural architectures that are exactly equivariant to continuous translations is an active field of research. It promises to benefit scientific computing…