4 citations · 6 across the 6 of their papers we have counts for
6 papers · 1 filter
SGPDFuse: Semantically-Guided Physics-Disentanglement General Multi-Modal Image Fusion
Haozhen Wei, Chengjun Jiang, Yutong Guo +4
Multimodal image fusion (MMIF) aims to integrate complementary sensor data into a single representation that preserves intrinsic scene reality while eliminating environmental inter…
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…
Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks
Zhiying Jiang, Xingyuan Li, Jinyuan Liu +2
Image stitching seamlessly integrates images captured from varying perspectives into a single wide field-of-view image. Such integration not only broadens the captured scene but al…
From Text to Pixels: A Context-Aware Semantic Synergy Solution for Infrared and Visible Image Fusion
Xingyuan Li, Yang Zou, Jinyuan Liu +4
With the rapid progression of deep learning technologies, multi-modality image fusion has become increasingly prevalent in object detection tasks. Despite its popularity, the inher…
AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware Robust Adversarial Training
Xingyuan Li, Jinyuan Liu, Long Ma +2
Monocular 3D object detection plays a pivotal role in the field of autonomous driving and numerous deep learning-based methods have made significant breakthroughs in this area. Des…