Improved Inference for Human Attribute Recognition using Historical Video Frames

  • 투고 : 2021.09.02
  • 심사 : 2021.09.16
  • 발행 : 2021.09.30

초록

Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

키워드

과제정보

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2021-2016-0-00312) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation). This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (NRF-2019R1F1A1055593).

참고문헌

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