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Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 2659-2667

Attentionnet: Aggregating weak directions for accurate object detection

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; ITERATIVE METHODS; NEURAL NETWORKS; OBJECT RECOGNITION;

EID: 84973889564     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.305     Document Type: Conference Paper
Times cited : (163)

References (28)
  • 20
    • 84973896506 scopus 로고    scopus 로고
    • Do more dropouts in pool5 feature maps for better object detection
    • abs/1409. 6911
    • Z. Shen and X. Xue. Do more dropouts in pool5 feature maps for better object detection. Computing Research Repository (CoRR), abs/1409. 6911, 2014.
    • (2014) Computing Research Repository (CoRR)
    • Shen, Z.1    Xue, X.2
  • 21
    • 84933585162 scopus 로고    scopus 로고
    • Very deep convolutional networks for large-scale image recognition
    • abs/1409. 1556
    • K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. Computing Research Repository (CoRR), abs/1409. 1556, 2014.
    • (2014) Computing Research Repository (CoRR)
    • Simonyan, K.1    Zisserman, A.2
  • 25
    • 84937797151 scopus 로고    scopus 로고
    • Joint training of a convolutional network and a graphical model for human pose estimation
    • abs/1406. 2984
    • J. Tompson, A. Jain, Y. LeCun, and C. Bregler. Joint training of a convolutional network and a graphical model for human pose estimation. Computing Research Repository (CoRR), abs/1406. 2984, 2014.
    • (2014) Computing Research Repository (CoRR)
    • Tompson, J.1    Jain, A.2    LeCun, Y.3    Bregler, C.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.