About me

I am an Applied Scientist at Amazon AGI. Before joining Amazon, I was a postdoctoral fellow in the School of Engineering and Applied Sciences at Harvard University, working with Prof. Hanspeter Pfister. I received my B.S., M.S., and Ph.D. from KAIST, advised by Prof. In So Kweon.  My research lies in computer vision and machine learning. I am particularly interested in audio-visual learning, multimodal learning, multi-task learning, and other related areas.

Journal Publications

• ENInst: Enhancing weakly-supervised low-shot instance segmentation
  JMoon Ye-Bin, Dongmin Choi, Yongjin Kwon, Junsik Kim, Tae-Hyun Oh
  Pattern Recognition, 2024
  [Paper]
  
  

• Weakly Supervised Contrastive Learning for Unsupervised Vehicle Reidentification
  Jongmin Yu, Hyeontaek Oh, Minkyung Kim, Junsik Kim†
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 (Early Access)
  [Paper]
  
  

• An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination
  Minkyung Kim, Jongmin Yu, Junsik Kim†, Tae-Hyun Oh, Jun Kyun Choi
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023 (Early Access)
  [Paper]
  
  

• Active Anomaly Detection Based on Deep One-Class Classification
  Minkyung Kim, Junsik Kim, Jongmin Yu, Jun Kyun Choi
  Pattern Recognition Letters, 2022
  [Paper]
  
  

• Learning to Localize Sound Source in Visual Scenes: Analysis and Applications
  Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang ,In So Kweon
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
  [Paper] [Project]
  
  

• Robust and Globally Optimal Manhattan Frame Estimation in Near Real Time
  Kyungdon Joo, Tae-Hyun Oh, Junsik Kim, In So Kweon
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
  [Paper] [Project]

Conference Proceedings

• Multimodal Learning for Embryo Viability Prediction in Clinical IVF
  Junsik Kim, Zhiyi Shi, Davin Jeong, Johannes Knittel, Helen Y. Yang, Yonghyun Song, Wanhua Li, Yicong Li,
  Dalit Ben-Yosef, Daniel Needleman, Hanspeter Pfister
  International Conference on Medical image computing and computer-assisted intervention (MICCAI), Oct. 2024
  [Paper][Project]

• MoRA: LoRA Guided Multi-Modal Disease Diagnosis with Missing Modality
  Zhiyi Shi, Junsik Kim, Wanhua Li, Yicong Li, Hanspeter Pfister
  International Conference on Medical image computing and computer-assisted intervention (MICCAI), Oct. 2024
  [Paper][Project]

• R^2-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding
  Ye Liu*, Jixuan He*, Wanhua Li, Junsik Kim, Donglai Wei, Hanspeter Pfister, Chang Wen Chen
  European Conference on Computer Vision (ECCV), Oct 2024
  [Paper][Project]

• Joint-Task Regularization for Partially Labeled Multi-Task Learning
  Kento Nishi*, Junsik Kim*, Wanhua Li, Hanspeter Pfister
  IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2024
  [Paper] [Project]

• Blurry Video Compression: A Trade-Off Between Visual Enhancement and Data Compression
  Dawit Mureja Argaw, Junsik Kim, In So Kweon
  IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2024
  [Paper]

• Sound Source Localization is All about Cross-Modal Alignment
  Arda Senocak*, Hyeonggon Ryu*, Junsik Kim*, Tae-Hyun Oh, Hanspeter Pfister, Joon Son Chung
  IEEE International Conference on Computer Vision (ICCV), Oct. 2023
  [Paper][Project]

• Event-Specific Audio-Visual Fusion Layers: A Simple and New Perspective on Video Understanding
  Arda Senocak*, Junsik Kim*, Tae-Hyun Oh, Dingzeyu Li, In So Kweon
  IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2023
  [Paper]

• Unsupervised Deep One-Class Classification with Adaptive Threshold based on Training Dynamics
  Minkyung Kim, Junsik Kim, Jongmin Yu, Jun Kyun Choi
  ICDM 2022 Workshop Deep Learning and Clustering (ICDMW), Nov 2022
  [Paper]

• ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound
  Domain Adaptation in Semantic Segmentation
  Fei Pan, Sungsu Hur, Seokju Lee, Junsik Kim, In So Kweon
  European Conference on Computer Vision (ECCV), Oct 2022
  [Paper] 

• Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification
  Jongmin Yu, Junsik Kim, Minkyung Kim, Hyeontaek Oh
  IEEE International Conference on Robotics and Automation (ICRA), May 2022
  [Paper] [Project]

• Learning Sound Localization Better from Semantically Similar Samples
  Arda Senocak*, Hyeonggon Ryu*, Junsik Kim*, In So Kweon (* equal contribution)
  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),  May 2022
  [Paper]

• Less Can Be More: Sound Source Localization With a Classification Model
  Arda Senocak*, Hyeonggon Ryu*, Junsik Kim*, In So Kweon (* equal contribution)
  IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2022
  [Paper]

• Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination
  Jongmin Yu, Hyeontaek Oh, Minkyung Kim, Junsik Kim
  NeurIPS 2021 Workshop DGMs Applications, Dec. 2021
  [Paper] [Project]

• Restoration of Video Frames From a Single Blurred Image With Motion Understanding
  Dawit Mureja Argaw, Junsik Kim, Francois Rameau, Chaoning Zhang, In So Kweon
  IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshop), Jun. 2021
  [Paper]

• Motion-blurred Video Interpolation and Extrapolation
  Dawit Mureja Argaw, Junsik Kim, Francois Rameau, In So Kweon
  AAAI Conference on Artificial Intelligence (AAAI), Feb. 2021
  [Paper]

• Optical Flow Estimation from a Single Motion-Blurred Image
  Dawit Mureja Argaw, Junsik Kim, Francois Rameau, JaeWon Cho, In So Kweon
  AAAI Conference on Artificial Intelligence (AAAI), Feb. 2021
  [Paper]

• ResNet or DenseNet? Introducing Dense Short-cuts to ResNet
  Chaoning Zhang*, Philipp Benz*, Dawit Mureja Argaw, Seokju Lee, Junsik Kim, Francois Rameau,
  Jean-Charles Bazin, In So Kweon
  IEEE Winter Conference on Applications of Computer Vision (WACV), Jan. 2021.
  [Paper]

• DeepPTZ: Deep Self-Calibration for PTZ Cameras
  Chaoning Zhang, Francois Rameau, Junsik Kim, Dawit Mureja Argaw, Jean-Charles Bazin, In So Kweon
  IEEE Winter Conference on Applications of Computer Vision (WACV), Mar. 2020.
  [Paper]

• Revisiting Residual Networks with Nonlinear Shortcuts
  Chaoning Zhang, Francois Rameau, Seokju Lee, Junsik Kim, Philipp Benz, Dawit Mureja Argaw,
  Jean-Charles Bazin, In So Kweon
  British Machine Vision Conference (BMVC), Sep. 2019 (spotlight)
  [Paper]

• Visuomotor Understanding for Representation Learning of Driving Scenes
  Seokju Lee, Junsik Kim, Tae-Hun Oh, Yongseop Jeong, Donggeun Yoo, Stephen Lin, In So Kweon
  British Machine Vision Conference (BMVC), Sep. 2019
  [Paper] [Project]

• Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images
  Junsik Kim, Tae-Hyun Oh, Seokju Lee, Fei Pan, In So Kweon
  IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2019
  [Paper] [Project]

• Part-based Player Identification using Deep Convolutional Representation and Multi-scale Pooling
  Arda Senocak, Tae-Hyun Oh, Junsik Kim, In So Kweon
  In CVSports workshop in conjunction with CVPR, Jun. 2018
  [Paper] 

• Learning to Localize Sound Source in Visual Scenes
  Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang, In So Kweon
  IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2018
  [Paper] [Project] 

• Co-domain Embedding using Deep Quadruplet Networks for Unseen Traffic Sign Recognition
  Junsik Kim, Seokju Lee, Tae-Hyun Oh, In So Kweon
  AAAI Conference on Artificial Intelligence (AAAI), Feb. 2018
  [Paper]

• VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
  Seokju Lee, Junsik Kim, Jae Shin Yoon, Seunghak Shin, Oleksandr Bailo, Namil Kim, Tae-Hee Lee,
  Hyun Seok Hong, Seung-Hoon Han, In So Kweon
  IEEE International Conference on Computer Vision (ICCV), Oct. 2017
  [Paper] [Project]

• Pixel-Level Matching for Video Object Segmentation Using Convolutional Neural Networks
  Jae Shin Yoon, Francois Rameau, Junsik Kim, Seokju Lee, Seunghak Shin, In So Kweon
  IEEE International Conference on Computer Vision (ICCV), Oct. 2017
  [Paper] [Project] 

• Globally Optimal Manhattan Frame Estimation in Real-time
  Kyungdon Joo, Tae-Hyun Oh, Junsik Kim, In So Kweon
  IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2016
  [Paper] [Project] 

Awards & Honors

• Best Poster Award, Workshop on What is Motion for? in conjuction with ECCV 2022

• Outstanding Reviewer Award,  International Conference on Learning Representations (ICLR) 2021

• Qualcomm Innovation Awards Sep. 2018

• Best Poster Presentation Award, IPIU Feb. 2018

• Magna Cum Laude, KAIST, Feb. 2012

• Honor Student Program, KAIST Sep. 2010 - Feb. 2012

• National Science and Engineering Scholarship, KOSAF Feb. 2008 - Feb. 2012

Academic Activities

Reviewer

International Journals

• Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 

• International Journal of Computer Vision (IJCV)

• Sensors

• The Visual Computer

• Electronics
  
  

International Conferences

• IEEE Conference on Computer Vision and Pattern Recognition (CVPR)    2018 - 

• IEEE International Conference on Computer Vision (ICCV)                        2019 -

• European Conference on Computer Vision (ECCV)                                    2018 -

• Conference on Neural Information Processing Systems (NeurIPS)            2020 -

• International Conference on Machine Learning (ICML)                               2020 -

• International Conference on Learning Representations (ICLR)                   2021 -

• AAAI Conference on Artificial Intelligence (AAAI)                                        2020 -

• British Machine Vision Conference (BMVC)                                                2019 -

• Winter Conference on Applications of Computer Vision (WACV)                2020 -

• Asia Conference on Computer Vision (ACCV)                                            2018 -

• Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023 -