Selective Refinement Network for High Performance Face Detection

7 Sep 2018 Cheng Chi Shifeng Zhang Junliang Xing Zhen Lei Stan Z. Li Xudong Zou

High performance face detection remains a very challenging problem, especially when there exists many tiny faces. This paper presents a novel single-shot face detector, named Selective Refinement Network (SRN), which introduces novel two-step classification and regression operations selectively into an anchor-based face detector to reduce false positives and improve location accuracy simultaneously... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Face Detection Annotated Faces in the Wild SRN AP 0.9987 # 1
Face Detection FDDB SRN AP 0.988 # 3
Face Detection PASCAL Face SRN AP 0.9909 # 1
Face Detection WIDER Face (Easy) SRN AP 0.959 # 3
Face Detection WIDER Face (Hard) SRN AP 0.896 # 5
Face Detection WIDER Face (Medium) SRN AP 0.948 # 3

Methods used in the Paper


METHOD TYPE
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