12 papers
H2AL: Hyperbolic Hierarchy-aware Aggregative Learning for Registration-based Few-shot Medical Image Segmentation
Jia Wang, Jiaming Cai, Zunying Hu +4
Registration-based Few-shot medical image segmentation (RFMIS) aims to generate pseudo-labels for unlabeled images by warping a labeled image through registration. However, existin…
DRFusion: Drift-Resilient Temporally Consistent Infrared-Visible Video Fusion
Xingyuan Li, Haoyuan Xu, Shulin Li +3
Infrared and visible video fusion is essential for achieving comprehensive perception in dynamic scenes. However, maintaining temporal consistency remains a formidable challenge. C…
Uncertainty-aware Spatial-Frequency Registration and Fusion for Infrared and Visible Images
Xingyuan Li, Haoyuan Xu, Xingyue Zhu +4
Infrared and Visible Image Fusion (IVIF) has shown promise in visual tasks under challenging environments, but fusion under unregistered conditions faces inherent misalignments. Cu…
UniFusion: A Unified Image Fusion Framework with Robust Representation and Source-Aware Preservation
Xingyuan Li, Songcheng Du, Yang Zou +3
Image fusion aims to integrate complementary information from multiple source images to produce a more informative and visually consistent representation, benefiting both human per…
Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset
Yang Zou, Jun Ma, Zhidong Jiao +3
Infrared image super-resolution (IISR) under real-world conditions is a practically significant yet rarely addressed task. Pioneering works are often trained and evaluated on simul…
Bridging Human Evaluation to Infrared and Visible Image Fusion
Jinyuan Liu, Xingyuan Li, Qingyun Mei +5
Infrared and visible image fusion (IVIF) integrates complementary modalities to enhance scene perception. Current methods predominantly focus on optimizing handcrafted losses and o…