72 citations · 191 across the 22 of their papers we have counts for
7 papers · 1 filter
Adversarial Semi-Supervised Domain Adaptation for Semantic Segmentation: A New Role for Labeled Target Samples
Marwa Kechaou, Mokhtar Z. Alaya, Romain Hérault +1
Adversarial learning baselines for domain adaptation (DA) approaches in the context of semantic segmentation are under explored in semi-supervised framework. These baselines involv…
Physically-admissible polarimetric data augmentation for road-scene analysis
Cyprien Ruffino, Rachel Blin, Samia Ainouz +4
Polarimetric imaging, along with deep learning, has shown improved performances on different tasks including scene analysis. However, its robustness may be questioned because of th…
Object Detection in the DCT Domain: is Luminance the Solution?
Benjamin Deguerre, Clement Chatelain, Gilles Gasso
Object detection in images has reached unprecedented performances. The state-of-the-art methods rely on deep architectures that extract salient features and predict bounding boxes…
Pixel-wise Conditioning of Generative Adversarial Networks
Cyprien Ruffino, Romain Hérault, Eric Laloy +1
Generative Adversarial Networks (GANs) have proven successful for unsupervised image generation. Several works extended GANs to image inpainting by conditioning the generation with…
Dilated Spatial Generative Adversarial Networks for Ergodic Image Generation
Cyprien Ruffino, Romain Hérault, Eric Laloy +1
Generative models have recently received renewed attention as a result of adversarial learning. Generative adversarial networks consist of samples generation model and a discrimina…
Fast object detection in compressed JPEG Images
Benjamin Deguerre, Clément Chatelain, Gilles Gasso
Object detection in still images has drawn a lot of attention over past few years, and with the advent of Deep Learning impressive performances have been achieved with numerous ind…