HAPNet: Toward Superior RGB-Thermal Scene Parsing via Hybrid, Asymmetric, and Progressive Heterogeneous Feature Fusion
HAPNet:通过混合、不对称和渐进式异构特征融合实现更优的RGB-热场景解析
机构 * College of Electronic and Information Engineering, Tongji University(同济大学电子与信息工程学院) ; Department of Computer Science and Engineering, Hong Kong University of Science and Technology(香港科技大学计算机科学与工程系) ; MSU-BIT-SMBU Joint Research Center of Applied Mathematics, Shenzhen MSU-BIT University(深圳MSU-BIT大学应用数学联合研究中心) ; Qingdao Innovation and Development Base, Harbin Institute of Technology (Weihai)(哈尔滨工业大学(威海)青岛创新与发展基地) ; Department of Control Science and Engineering, Harbin Institute of Technology(哈尔滨工业大学控制科学与工程系) ; Harbin Institute of Technology at Weihai(哈尔滨工业大学(威海)) ; Suzhou Research Institute, Harbin Institute of Technology(哈尔滨工业大学苏州研究所) ; Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University(莫斯科罗蒙诺夫莫斯科国立大学计算数学与自动化系)
AI总结 HAPNet通过混合、不对称和渐进式异构特征融合提升RGB-热场景解析性能,实现最佳效果。
Comments 16 pages, 4 figures. Accepted to the Biomimetic Intelligence and Robotics