Learning nighttime semantic segmentation the hard way

• Main Authors: LIU, Wenxi, CAI, Jiaxin, LI, Qi, LIAO, Chenyang, CAO, Jingjing, HE, Shengfeng, YU, Yuanlong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Nighttime semantic segmentation; dual-branch; hard class; pretext task; fusion refinement scheme; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/9801; https://ink.library.smu.edu.sg/context/sis_research/article/10801/viewcontent/NighttimeSemanticSeg_av.pdf
• Institution: Singapore Management University

Nighttime semantic segmentation is an important but challenging research problem for autonomous driving. The major challenges lie in the small objects or regions from the under-/over-exposed areas or suffer from motion blur caused by the camera deployed on moving vehicles. To resolve this, we propos...