whu-nercms at trecvid2021:instance search task
원문 초록
We will make a brief introduction of the experimental methods and results of the WHU-NERCMS in the TRECVID2021 in the paper. This year we participate in the automatic and interactive tasks of Instance Search (INS). For the automatic task, the retrieval target is divided into two parts, person retrieval, and action retrieval. We adopt a two-stage method including face detection and face recognition for person retrieval and two kinds of action detection methods consisting of three frame-based human-object interaction detection methods and two video-based general action detection methods for action retrieval. After that, the person retrieval results and action retrieval results are fused to initialize the result ranking lists. In addition, we make attempts to use complementary methods to further improve search performance. For interactive tasks, we test two different interaction strategies on the fusion results. We submit 4 runs for automatic and interactive tasks respectively. The introduction of each run is shown in Table 1. The official evaluations show that the proposed strategies rank 1st in both automatic and interactive tracks.
함께 살펴볼 논문
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Transforming faces into video stories -- VideoFace2.0
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods
Automated Visual Attention Detection using Mobile Eye Tracking in Behavioral Classroom Studies
Leveraging Simultaneous Usage of Edge GPU Hardware Engines for Video Face Detection and Recognition
Edge-GPU Based Face Tracking for Face Detection and Recognition Acceleration
Impact of Face Alignment on Face Image Quality
토론
이 논문과 연결된 포럼 글이 아직 없습니다.