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21 papers · 1 filter
MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image Fusion
Yanglin Deng, Tianyang Xu, Chunyang Cheng +2
In recent years, Multi-Modality Image Fusion (MMIF) has been applied to many fields, which has attracted many scholars to endeavour to improve the fusion performance. However, the…
CrossFuse: A Novel Cross Attention Mechanism based Infrared and Visible Image Fusion Approach
Hui Li, Xiao-Jun Wu
Multimodal visual information fusion aims to integrate the multi-sensor data into a single image which contains more complementary information and less redundant features. However…
Joint Self-supervised Depth and Optical Flow Estimation towards Dynamic Objects
Zhengyang Lu, Ying Chen
Significant attention has been attracted to deep learning-based depth estimates. Dynamic objects become the most hard problems in inter-frame-supervised depth estimates due to the…
Pyramid Frequency Network with Spatial Attention Residual Refinement Module for Monocular Depth Estimation
Zhengyang Lu, Ying Chen
Deep-learning-based approaches to depth estimation are rapidly advancing, offering superior performance over existing methods. To estimate the depth in real-world scenarios, depth…
A Survey for Deep RGBT Tracking
Zhangyong Tang, Tianyang Xu, Xiao-Jun Wu
Visual object tracking with the visible (RGB) and thermal infrared (TIR) electromagnetic waves, shorted in RGBT tracking, recently draws increasing attention in the tracking commun…
Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
Zhangyong Tang, Tianyang Xu, Hui Li +3
We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrare…