Two papers on image cropping and depth estimation will be published in Journal of Visual Communication and Image Representation.

• * Nyeong-Ho Shin, Seon-Ho Lee, Jinwon Ko, and Chang-Su Kim, “Image cropping based on order learning,” to appear in J. Vis. Commun. Image Represent., 2024.
• * Jinyoung Jun, Jae-Han Lee, and Chang-Su Kim, “Versatile depth estimator based on common relative depth estimation and camera-specific relative-to-metric depth conversion,” to appear in J. Vis. Commun. Image Represent., 2024.

Congratulations to our senior students Nyeong-Ho and Jinyoung!

We will present our papers on lane detection and face obfuscation at the ECCV conference in Milan, Italy this September.

• * Dongkwon Jin and Chang-Su Kim, “OMR: Occlusion-Aware Memory-Based Refinement for Video Lane Detection,” ECCV 2024.
• * Jintae Kim, Seungwon Yang, Seong-Gyun Jeong, and Chang-Su Kim, “Forbes: Face Obfuscation Rendering via Backpropagation Refinement Scheme,” ECCV 2024.

Congratulations to Dongkwon, Jintae, Seungwon, and Seong-Gyun!

Dongkwon will graduate MCL this summer. Including this ECCV paper, Dongkwon has published 7 CVPR/ICCV/ECCV papers. It is a great achievement. We are sure that Dr. Jin will have a successful career wherever he joins, be it an AI company or even the fashion industry.

MCL은 2025년 3월 입학 예정인 대학원생을 모집하고 있습니다. 컴퓨터비전, 인공지능에서 original research를 하고 싶은 학생은 김창수 교수(changsukim@korea.ac.kr)에게 연락바랍니다.

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!

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.