引き続き論文《FastReID:A Pytorch Toolbox for Real-world Person Re-identification》と《Deep Learning for Person Re-identification: A Survey and Outlook》。前者は主にそのネットワーク構築を学び、関連コードを読む。後者は更にこの課題を全面的に理解する以外に、この文章の中に少なくとも二つの観点がめって、思考に値します。第一に、新しい評価指標mINPの提出、第二にReIDをClosed-world と Open-worldに分けて、実際の応用から論証と研究を行います。
After reading some paper, I find that most paper are depth-supervised or a combination of depth, pose and stereo. And I don't find any paper only using pose-supervised.
The reason why not only using pose-supervised is that only considering large intensity gradient area will produce better results. And area with less texture will cause … Continue Reading ››