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View article: AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results Open
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable o…
View article: AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution
AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution Open
Recovering high-frequency details and textures from low-resolution images remains a fundamental challenge in super-resolution (SR), especially when real-world degradations are complex and unknown. While GAN-based methods enhance realism, t…
View article: ContextFormer: Redefining Efficiency in Semantic Segmentation
ContextFormer: Redefining Efficiency in Semantic Segmentation Open
Semantic segmentation assigns labels to pixels in images, a critical yet challenging task in computer vision. Convolutional methods, although capturing local dependencies well, struggle with long-range relationships. Vision Transformers (V…
View article: Complexity Experts are Task-Discriminative Learners for Any Image Restoration
Complexity Experts are Task-Discriminative Learners for Any Image Restoration Open
Recent advancements in all-in-one image restoration models have revolutionized the ability to address diverse degradations through a unified framework. However, parameters tied to specific tasks often remain inactive for other tasks, makin…
View article: Efficient Degradation-aware Any Image Restoration
Efficient Degradation-aware Any Image Restoration Open
Reconstructing missing details from degraded low-quality inputs poses a significant challenge. Recent progress in image restoration has demonstrated the efficacy of learning large models capable of addressing various degradations simultane…
View article: Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs
Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs Open
Modern smartphone camera quality heavily relies on the image signal processor (ISP) to enhance captured raw images, utilizing carefully designed modules to produce final output images encoded in a standard color space (e.g., sRGB). Neural-…
View article: The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report Open
This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this challenge is to super-resolve an input image with a magnificat…
View article: See More Details: Efficient Image Super-Resolution by Experts Mining
See More Details: Efficient Image Super-Resolution by Experts Mining Open
Reconstructing high-resolution (HR) images from low-resolution (LR) inputs poses a significant challenge in image super-resolution (SR). While recent approaches have demonstrated the efficacy of intricate operations customized for various …
View article: Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement
Gated Multi-Resolution Transfer Network for Burst Restoration and Enhancement Open
Burst image processing is becoming increasingly popular in recent years. However, it is a challenging task since individual burst images undergo multiple degradations and often have mutual misalignments resulting in ghosting and zipper art…
View article: Multimodal Medical Image Fusion using Guided Filter in NSCT Domain
Multimodal Medical Image Fusion using Guided Filter in NSCT Domain Open
Multimodal medical image fusion aims at minimizing the redundancy and collecting the relevant information using the input images acquired from different medical sensors. The main goal is to produce a single fused image having more informat…