Use of Generative Adversarial Network for Cross-Domain Change Detection. - Kousuke Yamaguchi; Kanji Tanaka 003; Takuma Sugimoto (CoRR, 2017)

Leveraging Object Proposals for Object-Level Change Detection. - Takuma Sugimoto; Kanji Tanaka 003; Kousuke Yamaguchi (Intelligent Vehicles Symposium, 2018)

An Experimental Study on Generative Adversarial Network and Visual Experience Mining for Domain Adaptive Change Detection. - Kousuke Yamaguchi; Kanji Tanaka 003; Yuusuke Kojima; Takuma Sugimoto (SMC, 2018)

Recursive Background Modeling with Place-specific Autoencoders for Large-scale Image Change Detection. - Kousuke Yamaguchi; Tanaka Kanji 003; Takuma Sugimoto; Rino Ide; Koji Takeda (ITSC, 2019)

From Comparison to Retrieval: Scalable Change Retrieval from Discriminatively Learned Deep Three-dimensional Neural Codes. - Kojima Yusuke; Tanaka Kanji 003; Naiming Yang; Yuji Hirota; Yamaguchi Kousuke (ITSC, 2019)

Place-specific Background Modeling Using Recursive Autoencoders. - Kousuke Yamaguchi; Kanji Tanaka 003; Takuma Sugimoto; Rino Ide; Koji Takeda (CoRR, 2019)

Fault-Diagnosing SLAM for Varying Scale Change Detection. - Takuma Sugimoto; Kousuke Yamaguchi; Kanji Tanaka 003 (CoRR, 2019)

Cross-Domain Change Object Detection Using Generative Adversarial Networks. - Takuma Sugimoto; Kanji Tanaka 003; Kousuke Yamaguchi (J. Robotics Mechatronics, 2019)

Fault-Diagnosing Monocular-SLAM for Scale-Aware Change Detection. - Takuma Sugimoto; Yamaguchi Kousuke; Zhongshan Bao; Minying Ye; Hiroki Tomoe; Tanaka Kanji 003 (SII, 2021)

Simultaneous Detection of Loop-Closures and Changed Objects. - Kanji Tanaka 003; Kousuke Yamaguchi; Takuma Sugimoto (J. Adv. Comput. Intell. Intell. Informatics, 2022)