NTIRE 2024 challenge on bracketing image restoration and enhancement: Datasets methods and results
Low-light photography presents significant challenges. Multi-image processing methods
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
have made numerous attempts to obtain high-quality photos yet remain unsatisfactory …
NTIRE 2022 burst super-resolution challenge
Burst super-resolution has received increased attention in recent years due to its
applications in mobile photography. By merging information from multiple shifted images of …
applications in mobile photography. By merging information from multiple shifted images of …
Generating aligned pseudo-supervision from non-aligned data for image restoration in under-display camera
Due to the difficulty in collecting large-scale and perfectly aligned paired training data for
Under-Display Camera (UDC) image restoration, previous methods resort to monitor-based …
Under-Display Camera (UDC) image restoration, previous methods resort to monitor-based …
Reversed image signal processing and RAW reconstruction. AIM 2022 challenge report
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 …
suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous …
Toward raw object detection: A new benchmark and a new model
In many computer vision applications (eg, robotics and autonomous driving), high dynamic
range (HDR) data is necessary for object detection algorithms to handle a variety of lighting …
range (HDR) data is necessary for object detection algorithms to handle a variety of lighting …
An end-to-end real-world camera imaging pipeline
Recent advances in neural camera imaging pipelines have demonstrated notable progress.
Nevertheless, the real-world imaging pipeline still faces challenges including the lack of joint …
Nevertheless, the real-world imaging pipeline still faces challenges including the lack of joint …
Self-supervised learning for real-world super-resolution from dual zoomed observations
In this paper, we consider two challenging issues in reference-based super-resolution
(RefSR),(i) how to choose a proper reference image, and (ii) how to learn real-world RefSR …
(RefSR),(i) how to choose a proper reference image, and (ii) how to learn real-world RefSR …
RAW-Adapter: Adapting Pre-trained Visual Model to Camera RAW Images
Abstract sRGB images are now the predominant choice for pre-training visual models in
computer vision research, owing to their ease of acquisition and efficient storage …
computer vision research, owing to their ease of acquisition and efficient storage …
Thermal Image Super-Resolution Challenge Results-PBVS 2024
This paper outlines the advancements and results of the Fifth Thermal Image Super-
Resolution challenge hosted at the Perception Beyond the Visible Spectrum CVPR 2024 …
Resolution challenge hosted at the Perception Beyond the Visible Spectrum CVPR 2024 …
SYENet: A simple yet effective network for multiple low-level vision tasks with real-time performance on mobile device
W Gou, Z Yi, Y **ang, S Li, Z Liu… - Proceedings of the …, 2023 - openaccess.thecvf.com
With the rapid development of AI hardware accelerators, applying deep learning-based
algorithms to solve various low-level vision tasks on mobile devices has gradually become …
algorithms to solve various low-level vision tasks on mobile devices has gradually become …