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Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection

Home Page: http://openaccess.thecvf.com/content_CVPR_2019/papers/Kim_Diversify_and_Match_A_Domain_Adaptive_Representation_Learning_Paradigm_for_CVPR_2019_paper.pdf

License: MIT License

Python 78.06% Shell 0.41% Cuda 8.85% C 11.83% C++ 0.48% MATLAB 0.36%

divmatch's Introduction

Staff Research Engineer at Qualcomm AI

  • Previously, Ph.D. at KAIST, Research Intern at Google, Visiting student at CMU [CV] [Homepage]
  • I am looking for a position as a research scientist in the US.

Research Interests [Details]

  • Computer vision and machine learning
  • CV: Person/vehicle re-identification, object tracking/recognition/detection/segmentation, gait/face recognition, image generation
  • ML: Domain adaption/generalization, meta-learning, normalization, few-shot learning, self-supervised learning, GAN

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