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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.
- 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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