4 citations · 8 across the 12 of their papers we have counts for
13 papers
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…
DMAligner: Enhancing Image Alignment via Diffusion Model Based View Synthesis
Xinglong Luo, Ao Luo, Zhengning Wang +5
Image alignment is a fundamental task in computer vision with broad applications. Existing methods predominantly employ optical flow-based image warping. However, this technique is…
RAW-Flow: Advancing RGB-to-RAW Image Reconstruction with Deterministic Latent Flow Matching
Zhen Liu, Diedong Feng, Hai Jiang +6
RGB-to-RAW reconstruction, or the reverse modeling of a camera Image Signal Processing (ISP) pipeline, aims to recover high-fidelity RAW data from RGB images. Despite notable progr…
Ultra High-Resolution Image Inpainting with Patch-Based Content Consistency Adapter
Jianhui Zhang, Sheng Cheng, Qirui Sun +7
In this work, we present Patch-Adapter, an effective framework for high-resolution text-guided image inpainting. Unlike existing methods limited to lower resolutions, our approach…
NTIRE 2024 Challenge on Night Photography Rendering
Egor Ershov, Artyom Panshin, Oleg Karasev +47
This paper presents a review of the NTIRE 2024 challenge on night photography rendering. The goal of the challenge was to find solutions that process raw camera images taken in nig…
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…
Learning Real-World Image De-Weathering with Imperfect Supervision
Xiaohui Liu, Zhilu Zhang, Xiaohe Wu +4
Real-world image de-weathering aims at removing various undesirable weather-related artifacts. Owing to the impossibility of capturing image pairs concurrently, existing real-world…
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…
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…
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…
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…
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,…
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…