2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IVASR-1.2
Paper Title Semantic Nighttime Image Segmentation via Illumination and Position Aware Domain Adaptation
Authors Junhan Peng, Jia Su, Capital Normal University, China; Yongqing Sun, Nippon Telegraph & Telephone, Japan; Zheng Wang, University of Tokyo, Japan; Chia-wen Lin, National Tsing Hua University, China
SessionMLR-APPL-IVASR-1: Machine learning for image and video analysis, synthesis, and retrieval 1
LocationArea D
Session Time:Monday, 20 September, 13:30 - 15:00
Presentation Time:Monday, 20 September, 13:30 - 15:00
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image & video analysis, synthesis, and retrieval
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Due to the lack of the annotated nighttime images, general image segmentation models trained on the daytime image dataset do not perform well in nighttime scenes. The difference of the illumination condition and the difficulty to obtain the position information between daytime and nighttime makes the nighttime image segmentation tough. As a result, this paper proposes an end-to-end nighttime segmentation network based on the following two points: 1) Utilizing illumination adaptation with the different illumination condition on the daytime or nighttime to close the distribution gap at the feature map level; 2) With the prior information about the position of each object in the outdoor scene, some classification errors could be corrected by incorporating the self-attention mechanism. The scheme is tested on the open-source nighttime dataset Dark Zurich and night driving, with a 2.5\% improvement compared to the base segmentation network.