Taeoh Kim Research Engineer / Technical Lead. at, NAVER Cloud Corp. As an engineer, I conduct research and development on technologies for video understanding and generation, and provide technical support for related services. E-mail: taeoh.kim [at] navercorp.com Google Scholar  /  Linkedin

News!

[Nov 2024] (New!) I gave a presentation in DAN 24, NAVER Conference [Session] [Press]
[Sep 2024] One Paper is accepted to NeurIPS 2024 (Video Anomaly Detection).
[Jul 2024] One Paper is accepted to ECCV 2024 (Oral) (Video Action Detection).
[Jan 2024] I won the N Innovation Award 2023, R&D Track [About] [Post].
[Aug 2023] One Paper is accepted to International Journal of Computer Vision (Image Processing).
[Feb 2023] One Paper is accepted to CVPR 2023 (Video Action Localization).
[Jan 2023] One Paper is accepted to ICLR 2023 (Spotlight) (Video Understanding).
[Nov 2022] One Paper is accepted to AAAI 2023 (Oral) (Video Representation Learning).
[Apr 2022] One Paper is accepted to Pattern Recognition (Video Anomaly Detection).
[Dec 2021] One Paper is accepted to IEEE Transactions on Image Processing (Video Deblurring).
[Nov 2021] One Paper is accepted to IEEE Transactions on Image Processing (Image Compression).

Publications

	Towards Multi-Domain Learning for Generalizable Video Anomaly Detection MyeongAh Cho, Taeoh Kim, Minho Shim, Dongyoon Wee, Sangyoun Lee NeurIPS, 2024 Paper / Project Page (Coming Soon)
	Classification Matters: Improving Video Action Detection with Class-Specific Attention Jinsung Lee, Taeoh Kim, Inwoong Lee, Minho Shim, Dongyoon Wee, Minsu Cho, Suha Kwak ECCV, 2024 (Oral Presentation, 2.3% Acceptance Rate) Paper / Project Page / Code
	A Nonlinear, Regularized, and Data-independent Modulation for Continuously Interactive Image Processing Network Hyeongmin Lee, Taeoh Kim, Hanbin Son, Sangwook Baek, Minsu Cheon, Sangyoun Lee Internation Journal of Computer Vision (IJCV, IF 19.5), 2023 Paper
	Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection Pilhyeon Lee, Taeoh Kim, Minho Shim, Dongyoon Wee, Hyeran Byun CVPR, 2023 Paper
	Exploring Temporally Dynamic Data Augmentation for Video Recognition Taeoh Kim, Jinhyung Kim, Minho Shim, Sangdoo Yun, Myunggu Kang, Dongyoon Wee, Sangyoun Lee ICLR, 2023 (Spotlight Presentation, Notable Top 25%) Paper / OpenReview
	Frequency Selective Augmentation for Video Representation Learning Jinhyung Kim, Taeoh Kim, Minho Shim, Dongyoon Han, Dongyoon Wee, Junmo Kim AAAI, 2023 (Oral Presentation) Paper
	Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features MyeongAh Cho, Taeoh Kim, Woo Jin Kim, Suhwan Cho, Sangyoun Lee Pattern Recognition (PR, IF 8.0), 2022 Paper
	Geometry-Aware Deep Video Deblurring via Recurrent Feature Refinement Taeoh Kim, Sangyoun Lee IEEE Transactions on Image Processing (TIP, IF 10.6), 2022 Paper
	Enhanced Standard Compatible Image Compression Framework based on Auxiliary Codec Networks Hanbin Son, Taeoh Kim, Hyeongmin Lee, Sangyoun Lee IEEE Transactions on Image Processing (TIP, IF 10.6), 2021 Paper
	Block-Attentive Subpixel Prediction Networks for Computationally Efficient Image Restoration Taeoh Kim, Chajin Shin, Sangjin Lee, Sangyoun Lee IEEE Access (IF 3.367), 2021 Paper
	Test-Time Adaptation for Out-of-distributed Image Inpainting Chajin Shin, Taeoh Kim, Sangjin Lee, Sangyoun Lee ICIP, 2021 Paper / Code
	AIM 2020 Challenge on Image Extreme Inpainting 2nd Place in the Image Inpainting Challenge Track 1: Classic Inpainting Evangelos Ntavelis, Andr´es Romero, Siavash Bigdeli, Radu Timofte, Zheng Hui, Xiumei Wang, Xinbo Gao, Chajin Shin, Taeoh Kim, Hanbin Son, Sangyoun Lee et al. ECCV Workshops (Advances in Image Manipulation (AIM)), 2020 Paper
	Learning Temporally Invariant and Localizable Features via Data Augmentation for Video Recognition 4th Place in the VIPriors Action Recognition Challenge Taeoh Kim*, Hyeongmin Lee*, MyeongAh Cho*, Ho Seong Lee, Dong Heon Cho, Sangyoun Lee (*Equal Contribution) ECCV Workshops (1st Visual Inductive Priors (VIPriors) for Data-Efficient Deep Learning Workshop), 2020 Paper
	Relational Deep Feature Learning for Heterogeneous Face Recognition MyeongAh Cho, Taeoh Kim, Ig-Jae Kim, Kyungjae Lee, Sangyoun Lee IEEE Transactions on Information Forensics and Security (IF 7.718), 2020 Paper
	Extrapolative-Interpolative Cycle- Consistency Learning For Video Frame Extrapolation Sangjin Lee, Hyeongmin Lee, Taeoh Kim, Sangyoun Lee ICIP, 2020 Paper
	AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolation Hyeongmin Lee, Taeoh Kim, Tae-Young Chung, Daehyun Pak, Yuseok Ban, Sangyoun Lee CVPR, 2020 Paper / Code
	Sampling Operator to Learn the Scalable Correlation Filter for Visual Tracking Minkyu Lee, Taeoh Kim, Yuseok Ban, Eungyeol Song, Sangyoun Lee IEEE Access (IF 3.367), 2019 Paper
	SF-CNN: A Fast Compression Artifacts Removal via Spatial-To-Frequency Convolutional Neural Networks Taeoh Kim, Hyeongmin Lee, Hanbin Son, Sangyoun Lee ICIP, 2019 Paper
	NIR-to-VIS Face Recognition via Embedding Relations and Coordinates of the Pairwise Features MyeongAh Cho, Tae-Young Chung, Taeoh Kim, Sangyoun Lee ICB, 2019 Paper
	Collabonet: Collaboration of Generative Models by Unsupervised Classification Hyeongmin Lee, Taeoh Kim, Eungyeol Song, Sangyoun Lee ICIP, 2018 Paper