Burst Image Super-Resolution

6 papers with code • 2 benchmarks • 1 datasets

Reconstruct a high-resolution image from a set of low-quality images, very like the multi-frame super-resolution task.

Datasets


Most implemented papers

Deep Burst Super-Resolution

goutamgmb/deep-burst-sr CVPR 2021

We propose a novel architecture for the burst super-resolution task.

Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

goutamgmb/deep-burst-sr ICCV 2021

The deep reparametrization allows us to directly model the image formation process in the latent space, and to integrate learned image priors into the prediction.

Unfolding the Alternating Optimization for Blind Super Resolution

greatlog/DAN NeurIPS 2020

More importantly, \textit{Restorer} is trained with the kernel estimated by \textit{Estimator}, instead of ground-truth kernel, thus \textit{Restorer} could be more tolerant to the estimation error of \textit{Estimator}.

Burst Image Restoration and Enhancement

akshaydudhane16/bipnet CVPR 2022

Our central idea is to create a set of pseudo-burst features that combine complementary information from all the input burst frames to seamlessly exchange information.

BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment

algolzw/bsrt 18 Apr 2022

To overcome the challenges in BurstSR, we propose a Burst Super-Resolution Transformer (BSRT), which can significantly improve the capability of extracting inter-frame information and reconstruction.