67 citations · 158 across the 10 of their papers we have counts for
26 papers
Generative Adversarial Learning via Kernel Density Discrimination
Abdelhak Lemkhenter, Adam Bielski, Alp Eren Sari +1
We introduce Kernel Density Discrimination GAN (KDD GAN), a novel method for generative adversarial learning. KDD GAN formulates the training as a likelihood ratio optimization pro…
A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
We propose a novel GAN training scheme that can handle any level of labeling in a unified manner. Our scheme introduces a form of artificial labeling that can incorporate manually…
Optical Flow Dataset Synthesis from Unpaired Images
Adrian Wälchli, Paolo Favaro
The estimation of optical flow is an ambiguous task due to the lack of correspondence at occlusions, shadows, reflections, lack of texture and changes in illumination over time. Th…
ISD: Self-Supervised Learning by Iterative Similarity Distillation
Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai +2
Recently, contrastive learning has achieved great results in self-supervised learning, where the main idea is to push two augmentations of an image (positive pairs) closer compared…
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
Abdelhak Lemkhenter, Paolo Favaro
Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discar…
Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation
Simon Jenni, Paolo Favaro
Current state-of-the-art methods cast monocular 3D human pose estimation as a learning problem by training neural networks on large data sets of images and corresponding skeleton p…