15 citations · 32 across the 10 of their papers we have counts for
17 papers
Unsupervised Restoration of Weather-affected Images using Deep Gaussian Process-based CycleGAN
Rajeev Yasarla, Vishwanath A. Sindagi, Vishal M. Patel
Existing approaches for restoring weather-degraded images follow a fully-supervised paradigm and they require paired data for training. However, collecting paired data for weather…
ART-SS: An Adaptive Rejection Technique for Semi-Supervised restoration for adverse weather-affected images
Rajeev Yasarla, Carey E. Priebe, Vishal Patel
In recent years, convolutional neural network-based single image adverse weather removal methods have achieved significant performance improvements on many benchmark datasets. Howe…
3SD: Self-Supervised Saliency Detection With No Labels
Rajeev Yasarla, Renliang Weng, Wongun Choi +2
We present a conceptually simple self-supervised method for saliency detection. Our method generates and uses pseudo-ground truth labels for training. The generated pseudo-GT label…
Network Architecture Search for Face Enhancement
Rajeev Yasarla, Hamid Reza Vaezi Joze, Vishal M Patel
Various factors such as ambient lighting conditions, noise, motion blur, etc. affect the quality of captured face images. Poor quality face images often reduce the performance of f…
Exploring Overcomplete Representations for Single Image Deraining using CNNs
Rajeev Yasarla, Jeya Maria Jose Valanarasu, Vishal M. Patel
Removal of rain streaks from a single image is an extremely challenging problem since the rainy images often contain rain streaks of different size, shape, direction and density. M…
Semi-Supervised Image Deraining using Gaussian Processes
Rajeev Yasarla, V. A. Sindagi, V. M. Patel
Recent CNN-based methods for image deraining have achieved excellent performance in terms of reconstruction error as well as visual quality. However, these methods are limited in t…