Visual Correspondence and its applications. e.g., Semantic Correspondence, Few-shot Segmentation, 3D Reconstruction, Novel View Synthesis, etc. Specifically, I am interested in effective model architecture for transformers or designing efficient methods for correspondence.
Generative Models. e.g., Diffusion Models, Image-to-Image Translation, etc.
Multimodal Learning. e.g., Zero-shot Segmentation, Text-guided Image Manipulation, etc.

Also, I'm always trying to study various fields not stated above for interdisciplinary research.

• Korea University, Seoul, Korea

  • M.S./Ph.D. Integrated Student in Computer Science and Engineering
  • Mar. 2022 - Present

• Yonsei University, Seoul, Korea

  • B.S. in Computer Science
  • Mar. 2018 - Feb. 2022

• Undergraduate Intern (Korea University CVLAB, Seoul, Korea)
  • Jan. 2021 - Feb. 2022
  • Advisor: Prof. Seungryong Kim

CATs++: Boosting Cost Aggregation with Convolutions and Transformers

Seokju Cho*, Sunghwan Hong*, and Seungryong Kim
IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI),
To be appeared (Impact Factor: 24.314).
[Project Page] [arXiv]

Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence

Sunghwan Hong, Jisu Nam, Seokju Cho, Susung Hong, Sangryul Jeon, Dongbo Min, and Seungryong Kim
Neural Information Processing Systems (NeurIPS), 2022.
[Project Page] [arXiv]

MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation

Junyoung Seo*, Gyuseong Lee*, Seokju Cho, Jiyoung Lee, Seungryong Kim
ArXiv Preprint, 2022.
[Project Page] [arXiv]

Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence

Sunghwan Hong*, Seokju Cho*, Seungryong Kim, Stephen Lin
ArXiv Preprint, 2022.
[arXiv]

Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation

Sunghwan Hong*, Seokju Cho*, Jisu Nam, Stephen Lin, and Seungryong Kim
European Conference on Computer Vision (ECCV), 2022.
[Project Page] [arXiv]

AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning

Jiwon Kim*, Kwangrok Ryoo*, Gyuseong Lee, Seokju Cho, Junyoung Seo, Daehwan Kim, Hansang Cho, and Seungryong Kim (Under Review)
ArXiv Preprint, 2021.
[arXiv]

CATs: Cost Aggregation Transformers for Visual Correspondence

Seokju Cho*, Sunghwan Hong*, Sangryul Jeon, Yunsung Lee, Kwanghoon Sohn, and Seungryong Kim
Neural Information Processing Systems (NeurIPS), 2021.
[Project Page] [arXiv] [Github]