News

[CVPR 2024] Depths, lines, Quality, and Segmentation

We will present our papers on depth refinement, semantic line detection, image quality assessment, and interactive image segmentation at the upcoming conference CVPR in Seattle this June.

  • * Jinyoung Jun, Jae-Han Lee, and Chang-Su Kim, “Masked Spatial Propagation Network for Sparsity-Adaptive Depth Refinement,” CVPR 2024.
  • * Jinwon Ko, Dongkwon Jin, and Chang-Su Kim, “Semantic Line Combination Detector,” CVPR 2024.
  • * Nyeong-Ho Shin, Seon-Ho Lee, and Chang-Su Kim, “Blind Image Quality Assessment Based on Geometric Order Learning,” CVPR 2024.
  • * Chaewon Lee, Seon-Ho Lee, and Chang-Su Kim, “MFP: Making Full Use of Probability Maps for Interactive Image Segmentation,” CVPR 2024.

Congratulations to Jinyoung, Jae-Han, Jinwon, Dongkwon, Nyeong-Ho, Seon-Ho, and Chaewon!

[ICLR 2024] Unsupervised order learning

We are pleased to announce that our new results on order learning will be presented in ICLR 2024.

  • Seon-Ho Lee, Nyeong-Ho Shin, and Chang-Su Kim, “Unsupervised order learning,” in Proc. ICLR, Vienna, Austria, May 2024.

Congratuluations to Seon-Ho and Nyeong-Ho!

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

  1. 1. Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee, and Chang-Su Kim, “Order learning and its application to age estimation,” ICLR 2020.
  2. 2. Seon-Ho Lee and Chang-Su Kim, “Deep repulsive clustering of ordered data based on order-identity decomposition” ICLR 2021.
  3. 3. Nyeong Ho Shin, Seon-Ho Lee, and Chang-Su Kim, “Moving window regression: A novel approach to ordinal regression,” CVPR 2022.
  4. 4. Seon-Ho Lee and Chang-Su Kim, “Order learning using partially ordered data via chainization,” ECCV 2022.
  5. 5. Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim, “Geometric order learning for rank estimation,” NeurIPS 2022.
  6. 6. Seon-Ho Lee, Nyeong-Ho Shin, and Chang-Su Kim, “Unsupervised order learning,” ICLR 2024.

The very first exploration of order learning (from fully supervised to unsupervised) is now complete, and the second stage started.

 

 

[2024] 인턴 모집

MCL에서 컴퓨터비전, 머신러닝, 인공지능에 관심있는 인턴을 모집합니다 (인턴쉽 기간: 2024.02.19~2024.02.29). 첨부 파일을 참고하여 참여를 희망하는 학생은 김창수 교수(cskim@mcl.korea.ac.kr)에게 연락 바랍니다.
장소 및 시간은 공학관 366호 – 오후 2시 ~ 3시 30분이며, 온라인 없이 오프라인으로만 진행합니다.
자세한 내용은 아래 첨부파일 확인하여 주시기 바랍니다.

MCL Intership 2024

[2023] 고근수 박사 카톨릭대학교 부임

MCL 졸업생인 고근수 박사가 2023년 2학기에 카톨릭대학교 인공지능학과에 부임했습니다. 축하합니다.

[ICCV 2023] Inpainting and lane detection

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.