[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.

2023 CVPR Junheum Park