연구동향 분석

앵커 프리 방법을 이용한 다중 크기 얼굴 검출기

이동렬 김윤 2020년

논문상세정보
인용/피인용
' 앵커 프리 방법을 이용한 다중 크기 얼굴 검출기' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Anchor free method
  • Deep learning
  • Face detection
  • Feature pyramid learning
  • Multi-scale detection
  • 다중 크기 검출
  • 딥 러닝
  • 앵커 프리 방법
  • 얼굴 검출
  • 특징 피라미드 학습
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
3,265 0

0.0%

' 앵커 프리 방법을 이용한 다중 크기 얼굴 검출기' 의 참고문헌

  • You Only Look Once : Unified, Real-Time Object Detection
    Redmon, J. [2016]
  • Yet even faster (yef) real-time object detection
  • Wider face : A face detection benchmark
    S. Yang [2016]
  • Very deep convolutional networks for large-scale image recognition
  • Unitbox: An advanced object detection network
    J. Yu [2016]
  • Ssh : Single stage headless face detector
    Najibi, M. [2017]
  • Ssd : Single shot multibox detector
    Liu, W. [2016]
  • Selective search for object recognition
  • S3fd : Single shot scale-invariant face detector
    Zhang, S. [2017]
  • Robust real-time face detection
    P. Viola [2004]
  • Robust face detection via learning small faces on hard images
    Zhang, Z. [2020]
  • Retinaface: Single-stage dense face localisation in the wild
  • Refineface: Refinement neural network for high performance face detection
  • Real-time face detection based on YOLO
    Yang, W. [2018]
  • Pyramidbox : A context-assisted single shot face detector
    Tang, X. [2018]
  • PoseNet: A structure-aware convolutional network for human pose estimation
    Yu Chen [2017]
  • Measuring the objectness of image windows
    B. Alexe [2012]
  • Mask R-CNN
    He, K. [2017]
  • Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
  • Labeled faces in the wild: A database forstudying face recognition in unconstrained environments
  • Joint face detection and alignment using multitask cascaded convolutional networks
  • Inverse attention guided deep crowd counting network
  • Fully Convolutional Networks for Semantic Segmentation
  • Focal loss for dense object detection
  • Finding tiny faces
    P. Hu [2017]
  • Feature pyramid networks for object detection
    Lin, T. Y. [2017]
  • Fddb: A benchmark for face detection in unconstrained settings
    Jain, Vidit [2010]
  • Fcos : Fully convolutional one-stage object detection
    Tian, Z. [2019]
  • Faster R-cnn: Towards Real-time Object Detection with Region ProposalNetworks
    Ren, S. [2015]
  • Face r-cnn
  • Face detection, pose estimation,and landmark localization in the wild
    X. Zhu [2012]
  • Face detection with the faster r-cnn
    H. Jiang [2017]
  • Face detection using surf cascade
    J. Li [2011]
  • Example-based learning for viewbased human face detection
    K.-K. Sung [1998]
  • Design of a Deep Face Detector by Mask R-CNN
  • Densebox : Unifying landmark localization with end to end object detection
  • Deep learning for generic object detection: A survey
    Liu, Li [2020]
  • Deep high-resolution representation learning for human pose estimation
    Sun, K. [2019]
  • DSFD: dual shot face detector
    Li, J. [2019]
  • Crowdnet: A deep convolutional network for dense crowd counting
  • CenterFace:Joint Face Detection and Alignment Using Face as Point
  • Anchor Free Network for Multi-Scale Face Detection
    Wang, C. [2018]