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20212026
most citedSpatially Adaptive Self-Supervised Learning for Real-World Image Denoising

4 citations · 12 across the 14 of their papers we have counts for

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14 papers

cs.CV2026

NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge

Aleksei Khalin, Egor Ershov, Artyom Panshin +46

This paper presents a review of the NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge. The objective of the competition was to merge a set of misaligned smartphone images…

cs.CV2026

The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

Xiang Chen, Hao Li, Jiangxin Dong +89

This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image restoration under diverse real-wo…

cs.CV2024

MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results

Yuekun Dai, Dafeng Zhang, Xiaoming Li +60

The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algor…

cs.CV2023★ 2 cited

Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes

Zhilu Zhang, Haoyu Wang, Shuai Liu +3

Merging multi-exposure images is a common approach for obtaining high dynamic range (HDR) images, with the primary challenge being the avoidance of ghosting artifacts in dynamic sc…

cs.CV2023

Beyond Image Borders: Learning Feature Extrapolation for Unbounded Image Composition

Xiaoyu Liu, Ming Liu, Junyi Li +4

For improving image composition and aesthetic quality, most existing methods modulate the captured images by striking out redundant content near the image borders. However, such im…

cs.CV2023★ 2 cited

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

Xiaohong Liu, Xiongkuo Min, Wei Sun +69

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement W…

cs.CV2023

Self-supervised Learning to Bring Dual Reversed Rolling Shutter Images Alive

Wei Shang, Dongwei Ren, Chaoyu Feng +3

Modern consumer cameras usually employ the rolling shutter (RS) mechanism, where images are captured by scanning scenes row-by-row, yielding RS distortions for dynamic scenes. To c…

cs.CV2023★ 4 cited

Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising

Junyi Li, Zhilu Zhang, Xiaoyu Liu +4

Significant progress has been made in self-supervised image denoising (SSID) in the recent few years. However, most methods focus on dealing with spatially independent noise, and t…

eess.IV2022

Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile AI & AIM 2022 challenge: Report

Andrey Ignatov, Radu Timofte, Jin Zhang +21

As mobile cameras with compact optics are unable to produce a strong bokeh effect, lots of interest is now devoted to deep learning-based solutions for this task. In this Mobile AI…

cs.CV2022

Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report

Andrey Ignatov, Grigory Malivenko, Radu Timofte +36

Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks. Thus…

cs.CV2022

Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

Andrey Ignatov, Radu Timofte, Shuai Liu +35

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In thi…

eess.IV2022★ 1 cited

Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report

Marcos V. Conde, Radu Timofte, Yibin Huang +40

Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous low-level…

cs.CV2022★ 3 cited

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

Furkan Kınlı, Sami Menteş, Barış Özcan +30

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…

eess.IV2021

Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report

Andrey Ignatov, Kim Byeoung-su, Radu Timofte +29

Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data…