59 citations · 105 across the 8 of their papers we have counts for
7 papers · 1 filter
Physically Inspired Dense Fusion Networks for Relighting
Amirsaeed Yazdani, Tiantong Guo, Vishal Monga
Image relighting has emerged as a problem of significant research interest inspired by augmented reality applications. Physics-based traditional methods, as well as black box deep…
NTIRE 2021 Depth Guided Image Relighting Challenge
Majed El Helou, Ruofan Zhou, Sabine Susstrunk +1
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalizati…
NTIRE 2020 Challenge on NonHomogeneous Dehazing
Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu +49
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results e…
Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks
Tiantong Guo, Hojjat S. Mousavi, Vishal Monga
Deep learning methods, in particular, trained Convolutional Neural Networks (CNN) have recently been shown to produce compelling results for single image Super-Resolution (SR). Inv…
Deep Networks with Shape Priors for Nucleus Detection
Mohammad Tofighi, Tiantong Guo, Jairam K. P. Vanamala +1
Detection of cell nuclei in microscopic images is a challenging research topic, because of limitations in cellular image quality and diversity of nuclear morphology, i.e. varying n…
Deep Image Super Resolution via Natural Image Priors
Hojjat S. Mousavi, Tiantong Guo, Vishal Monga
Single image super-resolution (SR) via deep learning has recently gained significant attention in the literature. Convolutional neural networks (CNNs) are typically learned to repr…
Orthogonally Regularized Deep Networks For Image Super-resolution
Tiantong Guo, Hojjat S. Mousavi, Vishal Monga
Deep learning methods, in particular trained Convolutional Neural Networks (CNNs) have recently been shown to produce compelling state-of-the-art results for single image Super-Res…