VISION & LEARNING LABORATORY

VISION & LEARNING LABORATORY

Chung-Ang University

VISION & LEARNING LABORATORY @ CAU

The laboratory was formed in Mar. 2020 and is led by Prof. Eunwoo Kim.

The aim of VISION & LEARNING LABORATORY at Chung-Ang University is to push the boundary of machine learning research by developing efficient, versatile, and optimal machine learning models, towards general-purpose artificial intelligence. We engage in research to explore methods that understand and learn any intellectual task that human beings can do.

Our research interests include efficient machine learning, automated machine learning, multi-modal learning, multi-task learning, continual learning, representation learning, and their applications to computer vision and robotics, but not limited to.

NEWS

  • [03/2025] Our paper on efficient continual learning is accepted to Neural Networks.
  • [02/2025] Our paper on multi-modal learning is accepted to CVPR 2025 (Highlight).
  • [01/2025] Our paper on self-corrective task planning is accepted to ICRA 2025.
  • [12/2024] Our paper on dataset condensation is accepted to Pattern Recognition Letters.
  • [11/2024] Our paper on neural radiance fields is accepted to IEEE Signal Processing Letters.
  • [10/2024] Our paper on continual learning is accepted to NeurIPS 2024 Workshop.
  • [07/2024] Our paper on active learning is accepted to IEEE Signal Processing Letters.
  • [06/2024] Our paper on task planning based on LLMs is accepted to IROS 2024.
  • [06/2024] Our paper on self-supervised learning is accepted to Pattern Recognition Letters.
  • [04/2024] Our paper on neural architecture search is accepted to IEEE Transactions on Image Processing.
  • [12/2023] Our paper on high-dynamic range imaging is accepted to ICASSP 2024.
  • [07/2023] Our paper on generation-based continual learning is accepted to ICCV 2023.
  • [07/2022] Our paper on task association in continual learning is accepted to ECCV 2022.