Megh Makwana

TL;DR: This paper reviews the first NTIRE challenge on video super-resolution (restoration of rich details in low-resolution video frames) with focus on proposed solutions and results and gauge the state-of-the-art in videosuper-resolution.

TL;DR: This paper reviews the NTIRE challenge on image colorization (estimating color information from the corresponding gray image) with focus on proposed solutions and results.

TL;DR: An end-to-end trainable deep-learning based framework for joint optimization of document enhancement and recognition, using a generative adversarial network (GAN) based framework to perform image denoising followed by deep back projection network (DBPN) for super-resolution.

TL;DR: A Robust Image Colorization using self-attention based Progressive Generative Adversarial Network (RIC-SPGAN) which consists of residual encoder-decoder (RED) network and a Self-att attention based progressive Generative network (SP-GAN) in a cascaded form to perform the denoising and colorization of the image.

TL;DR: A novel end-to-end coupled Denoising based Saliency Prediction with Generative Adversarial Network (DSAL-GAN) framework to address the problem of salient object detection in noisy images and demonstrates with comprehensive evaluation that the proposed framework outperforms several baseline saliency models on various performance benchmarks.