Geonmo Gu

Education

  • M.S. in Computer Vision from Korea Advanced Institute of Science and Technology (Mar. 2016 - Feb. 2018)
  • B.S. in Electrical and Electronic Engineering from Yonsei University (Mar. 2010 - Feb. 2016)

Experience

  • Data scientist at Amazon Web Services (Sep. 2024 - Present)
  • Research and Developement Engineer at NAVER (Feb. 2018 - Sep. 2024)

Publications

2024

  • Language-only Training of Zero-shot Composed Image Retrieval
  • Geonmo Gu*, Sanghyuk Chun*, Wonjae Kim, Yoohoon Kang, Sangdoo Yun
  • Computer Vision and Pattern Recognition (CVPR), 2024.
  • [paper] [code]

2023

  • Graphit: A Unified Framework for Diverse Image Editing Tasks
  • Geonmo Gu, Sanghyuk Chun, Wonjae Kim, HeeJae Jun, Sangdoo Yun, Yoohoon Kang
  • Open source project
  • [code]
  • CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
  • Geonmo Gu*, Sanghyuk Chun*, Wonjae Kim, HeeJae Jun, Yoohoon Kang, Sangdoo Yun
  • Computer Vision and Pattern Recognition Workshop (CVPRW), 2024.
  • [paper] [code]

2022

  • Granularity-aware Adaptation for Image Retrieval over Multiple Tasks
  • Jon Almazan, Byungsoo Ko, Geonmo Gu, Diane Larlus, Yannis Kalantidis
  • European Conference on Computer Vision (ECCV), 2022.
  • [paper]
  • Self-Distilled Hashing for Deep Image Retrieval
  • Young Kyun Jang, Geonmo Gu, Byungsoo Ko, Nam Ik Cho
  • European Conference on Computer Vision (ECCV), 2022.
  • [paper]
  • Large-scale Bilingual Language-Image Contrastive Learning
  • Byungsoo Ko*, Geonmo Gu*
  • International Conference on Learning Representations (ICLRW), 2022.
  • [paper] [code] [demo]
  • Towards Light-weight and Real-time Line Segment Detection
  • Geonmo Gu*, Byungsoo Ko*, SeoungHyun Go, Sung-Hyun Lee, Jingeun Lee, Minchul Shin
  • Association for the Advancement of Artificial Intelligence (AAAI), 2022. (Oral)
  • [paper] [code] [demo]

2021

  • Learning with Memory-based Virtual Classes for Deep Metric Learning
  • Byungsoo Ko*, Geonmo Gu*, Han-Gyu Kim
  • International Conference on Computer Vision (ICCV), 2021.
  • [paper] [code]
  • RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network
  • Minchul Shin, Yoonjae Cho, Byungsoo Ko, Geonmo Gu
  • arXiv, 2021.
  • [paper]
  • Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
  • Geonmo Gu*, Byungsoo Ko*, Han-Gyu Kim
  • Association for the Advancement of Artificial Intelligence (AAAI), 2021.
  • [paper] [code]

2020

  • Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning
  • Byungsoo Ko*, Geonmo Gu*
  • Computer Vision and Pattern Recognition (CVPR), 2020.
  • [paper] [code]
  • Symmetrical Synthesis for Deep Metric Learning
  • Geonmo Gu*, Byungsoo Ko*, Han-Gyu Kim
  • Association for the Advancement of Artificial Intelligence (AAAI), 2020.
  • [paper] [code]
  • Compounding the performance improvements of assembled techniques in a convolutional neural network
  • Jungkyu Lee, Taeryun Won, Tae Kwan Lee, Hyemin Lee, Geonmo Gu, Kiho Hong
  • arXiv, 2020.
  • [paper] [code]
TODO: update papers