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Tomoyuki Suzuki

Applied Research Scientist (Computer Vision)

at CyberAgent

Tomoyuki Suzuki is an Applied Research Scientist at CyberAgent.
His current research interest is computer vision for creative work, including video/image decomposition and representation learning for creative content.

He is also pursuing his Ph.D. at Keio University under the supervision of Prof. Yoshimitsu Aoki, where he works on efficient video recognition.

Previously, he was a research engineer at DeNA, working on CV/ML R&D in the mobility domain. He also worked as a part-time researcher at AIST, conducting research on video event anticipation and visual representation learning.

For more details, please refer to his CV.

International Conference

  • Tomoyuki Suzuki*, Kotaro Kikuchi, Kota Yamaguchi, “Fast Sprite Decomposition from Animated Graphics”, ECCV 2024. (acceptance rate 27.9%) [Paper] [Project]

  • Shoko Sawada, Tomoyuki Suzuki, Kota Yamaguchi, Masashi Toyoda, “Visual Explanation for Advertising Creative Workflow”, CHI EA 2024. (acceptance rate 33.9%) [Paper]

  • Tomoyuki Suzuki*, Hirokatsu Kataoka*, Yoshimitsu Aoki, Yutaka Satoh, “Anticipating Traffic Accidents with Adaptive Loss and Large-scale Incident DB”, CVPR 2018. (acceptance rate 29.6%) [Paper] [Poster]

  • Tomoyuki Suzuki, Takahiro Itazuri, Kensho Hara, Hirokatsu Kataoka, “Learning Spatiotemporal 3D Convolution with Video Order Self-Supervision”, IEEE ECCV Workshop on Person In Context, 2018. [Paper]

  • Tomoyuki Suzuki, Munetaka Minoguchi, Ryota Suzuki, Akio Nakamura, Kenji Iwata, Yutaka Satoh, Hirokatsu Kataoka, “Semantic Change Detection”, IEEE ICARCV, 2018.

  • Kaori Abe, Munetaka Minoguchi, Teppei Suzuki, Tomoyuki Suzuki, Naofumi Akimoto, Yue Qiu, Ryota Suzuki, Kenji Iwata, Yutaka Satoh, Hirokatsu Kataoka, “Fashion Culture Database: Construction of Database for World-wide Fashion Analysis”, IEEE ICARCV 2018.

Journals

  • Tomoyuki Suzuki, Yoshimitsu Aoki, “RetinaViT: Efficient Visual Backbone for Online Video Streams”, Sensors, 24 (17), 2024. [Link]

  • Tomoyuki Suzuki, Yoshimitsu Aoki, “Efficient Transformer-Based Compressed Video Modeling via Informative Patch Selection”, Sensors, 23 (1), 2022. [Link]

  • Tomoyuki Suzuki, Yoshimitsu Aoki, “Time-sequential action recognition using pose-centric learning for action-transition videos”, Journal of the Japan Society for Precision Engineering, 83 (12), 2017. [Link]

Articles

Talks

Slides

Kaggle

id: tomoyukun

Professional Activities

  • SSII Interactive & Spotlight Session Chair (2024), Vice Chair (2023)

Others