TY - GEN
T1 - Scene Recognition with Comprehensive Regions Graph Modeling
AU - Zeng, Haitao
AU - Chen, Gongwei
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Learning the regional contents of scenes comprehensively is key to scene recognition. Due to semantic diversity and spatial complexity in scene images, modeling based on these regional contents is challenging. The current works mainly focus on some small and partial regions of the scene, while ignoring the majority region of the scene. In contrast, we propose the Semantic Regional Graph modeling framework for the comprehensive selection of discriminative semantic regions in scenes. To explore the relations of these regions, we propose to model these regions in geometric aspect based on the graph model, and generate the discriminative representations for scene recognition. Experimental results demonstrate the effectiveness of our method, which achieves state-of-the-art performances on MIT67 and SUN397 datasets.
AB - Learning the regional contents of scenes comprehensively is key to scene recognition. Due to semantic diversity and spatial complexity in scene images, modeling based on these regional contents is challenging. The current works mainly focus on some small and partial regions of the scene, while ignoring the majority region of the scene. In contrast, we propose the Semantic Regional Graph modeling framework for the comprehensive selection of discriminative semantic regions in scenes. To explore the relations of these regions, we propose to model these regions in geometric aspect based on the graph model, and generate the discriminative representations for scene recognition. Experimental results demonstrate the effectiveness of our method, which achieves state-of-the-art performances on MIT67 and SUN397 datasets.
KW - Graph Neural Network
KW - Scene recognition
UR - https://www.scopus.com/pages/publications/85076857961
U2 - 10.1007/978-3-030-34113-8_52
DO - 10.1007/978-3-030-34113-8_52
M3 - 会议稿件
AN - SCOPUS:85076857961
SN - 9783030341121
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 630
EP - 641
BT - Image and Graphics - 10th International Conference, ICIG 2019, Proceedings, Part 3
A2 - Zhao, Yao
A2 - Lin, Chunyu
A2 - Barnes, Nick
A2 - Chen, Baoquan
A2 - Westermann, Rüdiger
A2 - Kong, Xiangwei
PB - Springer
T2 - 10th International Conference on Image and Graphics, ICIG 2019
Y2 - 23 August 2019 through 25 August 2019
ER -