We will present our image inpainting and video lane detection algorithms in ICCV 2023.

Keunsoo Ko and Chang-Su Kim, “Continuously Masked Transformer for Image Inpainting,” in Proc. ICCV, Paris, France, Oct. 2023.
Dongkwon Jin, Dahyun Kim, and Chang-Su Kim, “Recursive Video Lane Detection,” in Proc. ICCV, Paris, France, Oct. 2023.

Congratulations to Dr. Ko for this achievement! Dr. Ko has been quite productive this year. Soon he will be the second Prof. Ko from MCL and be a proud father of two children. By the way, the first Prof. Koh should make more effort in this regard.

Congratulations to Dongkwon and Dahyun! Excellent jobs.

We are happy to announce that our work on video interpolation and image compression will be presented in CVPR, Vancouver, Canada this June.

Junheum Park, Jintae Kim, Chang-Su Kim, “BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation,” in Proc. CVPR 2023.

Seungmin Jeon, Kwang Pyo Choi, Youngo Park, Chang-Su Kim, “Context-Based Trit-Plane Coding for Progressive Image Compression,” in Proc. CVPR 2023.

Big congratulations to Junheum, Jintae, Seungmin, and many thanks to our colleagues Kwang Pyo and Youngo!

Junheum is now an experienced interpolator, and Jintae is following. Seungmin’s paper writing is better than his mountain climbing. Anyway, good job!

Finally, to those MCL members who couldn’t survive the cruel and almost random culling of three-fourths of the papers: Let’s simply continue.

MCL에서는 2024년 2월에 대학원에 입학할 학생을 모집합니다. 연구분야는 컴퓨터 비전, 기계학습, 영상처리입니다.

관심 있는 사람은 김창수 교수(cskim@mcl.korea.ac.kr)에게 연락 바랍니다.

MCL에서 컴퓨터비전, 머신러닝, 인공지능에 관심있는 인턴을 모집합니다 (인턴쉽 기간: 2023.02.13~2023.02.24). 첨부 파일을 참고하여 참여를 희망하는 학생은 김창수 교수(cskim@mcl.korea.ac.kr)에게 연락 바랍니다.
온라인으로 진행할 예정이며, 오프라인 참석도 가능합니다. Zoom link 및 오프라인 장소는 추후 공지 예정입니다.

MCL Intership 2023

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본 모집은 마감 하였습니다.
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Our paper on order learning will be presented in Neurips 2022.

Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim, “Geometric order learning for rank estimation,” in Proc. NeurIPS, New Orleans, Louisiana, Nov. 2022.

Order learning is a new concept that we proposed in a series of papers:

1. Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee, and Chang-Su Kim, “Order learning and its application to age estimation,” ICLR 2020.

2. Seon-Ho Lee and Chang-Su Kim, “Deep repulsive clustering of ordered data based on order-identity decomposition” ICLR 2021.

3. Nyeong Ho Shin, Seon-Ho Lee, and Chang-Su Kim, “Moving window regression: A novel approach to ordinal regression,” CVPR 2022.

4. Seon-Ho Lee and Chang-Su Kim, “Order learning using partially ordered data via chainization,” ECCV 2022.

5. Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim, “Geometric order learning for rank estimation,” NeurIPS 2022.

It has been a productive year for Ho brothers. Congratulations!