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DeeperVision and DeepInsight Solutions. Junjie Yan*, Naiyan Wang*, Yinan Yu, Linjiao Zhao, Stan Z. Li, Dit -Yan Yeung * denotes equal contribution. DeeperVision Classification. Deeper network always helps. DeeperVision Classification. Nesterov method based optimization
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DeeperVision and DeepInsight Solutions Junjie Yan*, Naiyan Wang*, Yinan Yu, Linjiao Zhao, Stan Z. Li, Dit-Yan Yeung * denotes equal contribution
DeeperVision Classification • Deeper network always helps
DeeperVision Classification • Nesterov method based optimization • With large momentum and Nesterov based optimization method, the algorithm could smooth out the optimization path. • It can improve top 1 accuracy by 0.8%
DeeperVision Classification • More findings… • Slow down the speed of data abstraction (stride, kernel size, etc.) • More complicated data augmentations • Spatial Pyramid Pooling (SPP) • Our final results • Single net: Top 5 error: 10.5% • Ensemble 5 nets: Top 5 error: 9.5%
Deep Insight Detection Region proposal + CNN feature extraction • Selective Search + Structural Edge [1] for region proposal. • 7/8/9 Convolution Layers + SPM +2 Fully Connected Layers. • Deeper Models need more tuning iterations. • Better (Deeper) Classification CNN always helps Detection. [1]C. Lawrence Zitnick and Piotr Dollár Edge Boxes: Locating Object Proposals from Edges ECCV 2014
Diagnosis Experiments (on 2013-val2 ) Original RCNN 31.4 + 9conv + SPM 36.6 + more iterations 39.2 + Structural Edge Proposal 40.1 + 7/8/9 Conv Ensemble 40.7 + CLS Context 42.0
Our Final Result • We have the best single model (40.2 mAP V.S. the 38.0 mAP of GoogLeNet) • We use a non-optimal ensemble method when submitting result. A better ensemble method leads to a 42.0 mAPon val2 after the competition. • Keeps improving…
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