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Person Search

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
2
보존된 평가 기록
31

Person Search is a task which aims at matching a specific person among a great number of whole scene images.

Source: Re-ID Driven Localization Refinement for Person Search

기법

관련 논문에서 소개한 기법입니다. 이 태스크에서의 평가 여부는 평가 결과에서 확인하세요.

AlignPS

AlignPS, or Feature-Aligned Person Search Network, is an anchor-free framework for efficient person search. The model employs the typical architecture of an anchor-free detection model (i.e., FCOS). An aligned feature aggregation (AFA) module is designed to make the model focus more on the re-id subtask. Specifically, AFA reshapes some building blocks of FPN to overcome the issues of region and scale misalignment in re-id feature learning. A deformable convolution is exploited to make the re-id embeddings adaptively aligned with the foreground regions. A feature fusion scheme is designed to better aggregate features from different FPN levels, which makes the re-id features more robust to scale variations. The training procedures of re-id and detection are also optimized to place more emphasis on generating robust re-id embeddings.

Efficient Person Search: An Anchor-Free Approach

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