1 citations · 4 across the 13 of their papers we have counts for
14 papers
When Simplicity Wins: Bottleneck-Aware Context Modeling for Lightweight Semantic Segmentation
Mian Muhammad Naeem Abid, Nancy Mehta, Zongwei Wu +1
Semantic segmentation demands a careful balance between accuracy, efficiency, and scalability, which remains difficult to achieve for high-resolution imagery. Convolutional network…
Experts-Guided Unbalanced Optimal Transport for ISP Learning from Unpaired and/or Paired Data
Georgy Perevozchikov, Nancy Mehta, Egor Ershov +1
Learned Image Signal Processing (ISP) pipelines offer powerful end-to-end performance but are critically dependent on large-scale paired raw-to-sRGB datasets. This reliance on cost…
AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
George Ciubotariu, Florin-Alexandru Vasluianu, Zhuyun Zhou +44
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…
DiTVR: Zero-Shot Diffusion Transformer for Video Restoration
Sicheng Gao, Nancy Mehta, Zongwei Wu +1
Video restoration aims to reconstruct high quality video sequences from low quality inputs, addressing tasks such as super resolution, denoising, and deblurring. Traditional regres…
Modulate and Reconstruct: Learning Hyperspectral Imaging from Misaligned Smartphone Views
Daniil Reutsky, Daniil Vladimirov, Yasin Mamedov +4
Hyperspectral reconstruction (HSR) from RGB images is a highly promising direction for accurate color reproduction and material color measurement. While most existing approaches re…
LeMoRe: Learn More Details for Lightweight Semantic Segmentation
Mian Muhammad Naeem Abid, Nancy Mehta, Zongwei Wu +1
Lightweight semantic segmentation is essential for many downstream vision tasks. Unfortunately, existing methods often struggle to balance efficiency and performance due to the com…
Color Matching Using Hypernetwork-Based Kolmogorov-Arnold Networks
Artem Nikonorov, Georgy Perevozchikov, Andrei Korepanov +4
We present cmKAN, a versatile framework for color matching. Given an input image with colors from a source color distribution, our method effectively and accurately maps these colo…
AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution
Cansu Korkmaz, Nancy Mehta, Radu Timofte
Recovering high-frequency details and textures from low-resolution images remains a fundamental challenge in super-resolution (SR), especially when real-world degradations are comp…
ContextFormer: Redefining Efficiency in Semantic Segmentation
Mian Muhammad Naeem Abid, Nancy Mehta, Zongwei Wu +1
Semantic segmentation assigns labels to pixels in images, a critical yet challenging task in computer vision. Convolutional methods, although capturing local dependencies well, str…
Complexity Experts are Task-Discriminative Learners for Any Image Restoration
Eduard Zamfir, Zongwei Wu, Nancy Mehta +4
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…
Efficient Degradation-aware Any Image Restoration
Eduard Zamfir, Zongwei Wu, Nancy Mehta +3
Reconstructing missing details from degraded low-quality inputs poses a significant challenge. Recent progress in image restoration has demonstrated the efficacy of learning large…
Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs
Georgy Perevozchikov, Nancy Mehta, Mahmoud Afifi +1
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 ima…
The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report
Bin Ren, Yawei Li, Nancy Mehta +129
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 cha…
See More Details: Efficient Image Super-Resolution by Experts Mining
Eduard Zamfir, Zongwei Wu, Nancy Mehta +2
Reconstructing high-resolution (HR) images from low-resolution (LR) inputs poses a significant challenge in image super-resolution (SR). While recent approaches have demonstrated t…