00/00
Papers
FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration
Author：Hao Li, Xiang Chen, Jiangxin Dong, Jinhui Tang, Jinshan Pan
Year：2025
Type：ICCV
Publication：IEEE International Conference on Computer Vision (ICCV)
Datasets
Competition
Ended
Mobile AI 2025 Challenges
Over the past years, mobile AI-based applications are becoming more and more ubiquitous. Various deep learning models can now be found on any mobile device, starting from smartphones running portrait segmentation, image enhancement, face recognition and natural language processing models, to smart-TV boards coming with sophisticated image super-resolution algorithms.
Ended
MIPI 2025 Challenges
Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of Mobile Intelligent Photography and Imaging (MIPI).
Ended
AIM 2025 Challenges
Image manipulation is a key computer vision tasks, aiming at the restoration of degraded image content, the filling in of missing information, or the needed transformation and/or manipulation to achieve a desired target (with respect to perceptual quality, contents, or performance of apps working on such images).
In Progress
NTIRE 2026 Challenges
Image restoration, enhancement and manipulation are key computer vision tasks, aiming at the restoration of degraded image content, the filling in of missing information, or the needed transformation and/or manipulation to achieve a desired target (with respect to perceptual quality, contents, or performance of apps working on such images). Recent years have witnessed an increased interest from the vision and graphics communities in these fundamental topics of research.
Journal
GIScience & Remote Sensing | Remote Sensing in Cloudy and Rainy Environments: Challenges, Advances, and Applications
Cloudy and rainy environments are common in tropical, subtropical, and other regions frequently affected by cloud cover and rainfall. These challenging conditions pose significant obstacles to remote sensing data acquisition, processing, and applications, while also motivating innovation in methodologies and technologies.
IEEE JSTARS | Advances in Multimodal Transfer Learning for Remote Sensing: Theories, Methods, and Applications
Remote sensing is witnessing an unprecedented data revolution, marked by the explosive growth of heterogeneous Earth Observation (EO) data from diverse sensors—optical, SAR, LiDAR, hyperspectral, and thermal—across multiple resolutions.
Ocean Engineering | Multimodal 3D Perception for Underwater Engineering: Acoustics, Optics and Integrated Solutions
Accurate 3D perception in underwater environments has become a critical requirement for various ocean engineering tasks such as subsea infrastructure inspection, autonomous navigation of underwater vehicles, habitat mapping, and environmental monitoring.
Pattern Recognition | Foundation Models and Prompting for Visual Tasks in Harsh Conditions
The emergence of foundation models (e.g., CLIP, DINO, SAM, BLIP, Segment Anything, and Diffusion Models) has revolutionized visual representation learning, enabling zero-shot transfer and unified modeling across diverse tasks. However, their robustness and adaptability under harsh visual conditions—such as extreme low-light, fog, underwater, motion blur, and low-resolution domains—remain under-explored and highly application-dependent.
