World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
26087
World Ranking
9010
National Ranking
3824

Overview

Joon-Young Lee is affiliated with Adobe Systems in the United States, focusing primarily on research within the field of Computer Science. Their work spans several subfields, notably Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Aerospace Engineering, and Signal Processing.

Their research topics cover a broad range of areas, including:

  • Advanced Image and Video Retrieval Techniques
  • Visual Attention and Saliency Detection
  • Video Analysis and Summarization
  • Multimodal Machine Learning Applications
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning

Joon-Young Lee has contributed to numerous publications with a significant number appearing in top venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Creativity and Cognition

Some notable recent papers featuring Lee's research include:

  • "A Simple and Light-Weight Attention Module for Convolutional Neural Networks," 2020, International Journal of Computer Vision
  • "Hierarchical Memory Matching Network for Video Object Segmentation," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Per-Clip Video Object Segmentation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Space-Time Memory Networks for Video Object Segmentation With User Guidance," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "VITA: Video Instance Segmentation via Object Token Association," 2022, arXiv (Cornell University)

Collaboration has been a consistent aspect of Lee's career. Frequent co-authors include:

  • Seoung Wug Oh
  • In So Kweon
  • Sanghyun Woo
  • Fabian Caba Heilbron
  • Seon Joo Kim

Their work reflects a sustained engagement with cutting-edge topics in computer vision and machine learning through both conference and journal publications, emphasizing video object segmentation, attention mechanisms in neural networks, and multimodal learning applications.

Best Publications

  • CBAM: Convolutional Block Attention Module

    Sanghyun Woo;Jongchan Park;Joon-Young Lee;In So Kweon

  • Video Object Segmentation Using Space-Time Memory Networks

    Seoung Wug Oh;Joon-Young Lee;Ning Xu;Seon Joo Kim

  • Fast Video Object Segmentation by Reference-Guided Mask Propagation

    Seoung Wug Oh;Joon-Young Lee;Kalyan Sunkavalli;Seon Joo Kim

  • CBAM: Convolutional Block Attention Module

    Sanghyun Woo;Jongchan Park;Joon-Young Lee;In So Kweon

  • Learning a Deep Convolutional Network for Light-Field Image Super-Resolution

    Youngjin Yoon;Hae-Gon Jeon;Donggeun Yoo;Joon-Young Lee

  • BAM: Bottleneck Attention Module

    Jongchan Park;Sanghyun Woo;Joon-Young Lee;In So Kweon

  • Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks

    Yinda Zhang;Shuran Song;Ersin Yumer;Manolis Savva

  • Robust High Dynamic Range Imaging by Rank Minimization

    Tae-Hyun Oh;Joon-Young Lee;Yu-Wing Tai;In So Kweon

  • Light-Field Image Super-Resolution Using Convolutional Neural Network

    Youngjin Yoon;Hae-Gon Jeon;Donggeun Yoo;Joon-Young Lee

  • AttentionNet: Aggregating Weak Directions for Accurate Object Detection

    Donggeun Yoo;Sunggyun Park;Joon-Young Lee;Anthony S. Paek

  • Distort-and-Recover: Color Enhancement Using Deep Reinforcement Learning

    Jongchan Park;Joon-Young Lee;Donggeun Yoo;In So Kweon

  • Deep Video Inpainting

    Dahun Kim;Sanghyun Woo;Joon-Young Lee;In So Kweon

  • Video Panoptic Segmentation

    Dahun Kim;Sanghyun Woo;Joon-Young Lee;In So Kweon

  • A Simple and Light-Weight Attention Module for Convolutional Neural Networks

    Jongchan Park;Sanghyun Woo;Joon-Young Lee;In So Kweon

  • URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark

    Seonguk Seo;Joon-Young Lee;Bohyung Han

  • Color Transfer Using Probabilistic Moving Least Squares

    Youngbae Hwang;Joon-Young Lee;In So Kweon;Seon Joo Kim

  • Multi-scale pyramid pooling for deep convolutional representation

    Donggeun Yoo;Sunggyun Park;Joon-Young Lee;In So Kweon

  • Tracking Anything with Decoupled Video Segmentation

    Unknown

  • Hierarchical Memory Matching Network for Video Object Segmentation

    Hongje Seong;Seoung Wug Oh;Joon-Young Lee;Seongwon Lee

  • Hierarchical Memory Matching Network for Video Object Segmentation

    Hongje Seong;Seoung Wug Oh;Joon-Young Lee;Seongwon Lee

  • High Quality Shape from a Single RGB-D Image under Uncalibrated Natural Illumination

    Yudeog Han;Joon-Young Lee;In So Kweon

  • Onion-Peel Networks for Deep Video Completion

    Seoung Wug Oh;Sungho Lee;Joon-Young Lee;Seon Joo Kim

  • Simple and universal platform for logic gate operations based on molecular beacon probes.

    Ki Soo Park;Myung Wan Seo;Cheulhee Jung;Joon Young Lee

  • VITA: Video Instance Segmentation via Object Token Association

    Unknown

  • Time-of-Flight Sensor Calibration for a Color and Depth Camera Pair

    Jiyoung Jung;Joon-Young Lee;Yekeun Jeong;In So Kweon

  • Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias

    Rameswar Panda;Jianming Zhang;Haoxiang Li;Joon-Young Lee

Frequent Co-Authors

In So Kweon
In So Kweon Korea Advanced Institute of Science and Technology
Zhe Lin
Zhe Lin Adobe Systems (United States)
Kalyan Sunkavalli
Kalyan Sunkavalli Adobe Systems (United States)
Hailin Jin
Hailin Jin Adobe Systems (United States)
Zhaowen Wang
Zhaowen Wang Adobe Systems (United States)
Xiaohui Shen
Xiaohui Shen ByteDance
Bernard Ghanem
Bernard Ghanem King Abdullah University of Science and Technology
Pablo Arbeláez
Pablo Arbeláez Universidad de Los Andes
Bohyung Han
Bohyung Han Seoul National University
Yu-Wing Tai
Yu-Wing Tai Hong Kong University of Science and Technology

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