From the 1 of 178 linked papers with an AI index.
54 citations · 58 across the 73 of their papers we have counts for
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Restore Anything Model via Efficient Degradation Adaptation
Bin Ren, Eduard Zamfir, Zongwei Wu +6
With the proliferation of mobile devices, the need for an efficient model to restore any degraded image has become increasingly significant and impactful. Traditional approaches ty…
XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
Yuedong Tan, Zongwei Wu, Yuqian Fu +7
Multimodal sensing has proven valuable for visual tracking, as different sensor types offer unique strengths in handling one specific challenging scene where object appearance vari…
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results
Maksim Smirnov, Aleksandr Gushchin, Anastasia Antsiferova +29
Video quality assessment (VQA) is a crucial task in the development of video compression standards, as it directly impacts the viewer experience. This paper presents the results of…
Enhanced Super-Resolution Training via Mimicked Alignment for Real-World Scenes
Omar Elezabi, Zongwei Wu, Radu Timofte
Image super-resolution methods have made significant strides with deep learning techniques and ample training data. However, they face challenges due to inherent misalignment betwe…
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results
Ivan Molodetskikh, Artem Borisov, Dmitriy Vatolin +24
This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with E…
Steering Prediction via a Multi-Sensor System for Autonomous Racing
Zhuyun Zhou, Zongwei Wu, Florian Bolli +5
Autonomous racing has rapidly gained research attention. Traditionally, racing cars rely on 2D LiDAR as their primary visual system. In this work, we explore the integration of an…