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第４６回コンピュータ・ビジョン勉強会＠関東（前編）
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- 4. DenseASPP Cycle-Shape-GAN M. Yang, et.al. ” DenseASPP for Semantic Segmentation in Street Scenes Z. Zhang, et. al. ”Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network”
- 5. DenseASPP M. Yang, et.al. ” DenseASPP for Semantic Segmentation in Street Scenes” CVF URL http://openaccess.thecvf.com/content_cvpr_2018/papers/Yang _DenseASPP_for_Semantic_CVPR_2018_paper.pdf https://github.com/masataka46/DenseASPP-chainer
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- 7. DenseNet DenseASPP DenseNet ASPP G.Huang, et. al. “Densely Connected Convolutional Networks” CVPR2017 l
- 8. ASPP DenseASPP DenseNet ASPP F.Yu, et. al. “Multi-scale context aggregation by dilated convolutions ” ICLR2016 l Atrous convolution dilated convolution l http://deeplearning.net/software/the ano/tutorial/conv_arithmetic.html
- 9. ASPP DenseASPP DenseNet ASPP ldilation rate L. Chen, et. al. “Rethinking Atrous Convolution for Semantic Image Segmentation”
- 10. ASPP DenseASPP DenseNet ASPP L.Chen, et. al. “Rethinking Atrous Convolution for Semantic Image Segmentation” l Atrous convolution
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- 12. ASPP DenseASPP DenseNet ASPP M.Yang, et. al. ” DenseASPP for Semantic Segmentation in Street Scenes” CVPR2018 l Atrous convolution Densely
- 13. ASPP DenseASPP DenseNet ASPP M.Yang, et. al. ” DenseASPP for Semantic Segmentation in Street Scenes” CVPR2018 l Atrous convolution Densely
- 14. DenseASPP atrous-conv dilation rate 3dilation rate6 3×2 + 6×2 + 1 = 19 (pixel)
- 15. DenseASPP atrous conv dilation rate3, 6, 12, 18, 19 atrous conv 3×2 + 6×2 + 12×2 + 18×2 + 24×2 + 1 = 127 (pixel)
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- 19. Chainer https://github.com/masataka46/DenseASPP-chainer Atrous convolution Dilatedconvolution L.DilatedConvolution2D DilatedConv concat
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- 21. DenseASPP 1 epoch 50epoch 50 epoch ground truth ground truth
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- 23. Cycle-Shape-GAN Z. Zhang, et.al. ”Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network” arXiv URL https://arxiv.org/abs/1802.09655 Chainer https://github.com/masataka46/Cycle-Shape-GAN-chainer
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- 25. Cycle-GAN GAN J. Y. Zhu,et. al. Unpaired Image-to-Image Translation using Cycle- Consistent Adversarial Networks • Generator X • Generator Y
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- 30. Chainer https://github.com/masataka46/Cycle-Shape-GAN-chainer Cycle-GAN Cycle-Shape-GAN Generator X GeneratorY Discriminator X Discriminator Y Generator X Generator Y Discriminator X Discriminator Y Segmentor X Segmentor Y Segmentor Class Class Class Class Class Class Class Class Class Class
- 31. Chainer Cycle-GAN Cycle-Shape-GAN Segmentor loss !"#"$%= !$'( + !*+*%, + !-,.!"#"$% = !$'( + !*+*%, https://github.com/masataka46/Cycle-Shape-GAN-chainer
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- 34. Cycle-GAN Cycle-GAN Cycle-Shape-GAN10 epoch10 epoch → → → → → → Cycle-GAN Cycle-Shape-GAN → → → → → →
- 35. Cycle-Shape-GAN segmentation Cycle-Shape-GAN Cycle-Shape-GAN1epoch 60 epoch (1 epoch) 60 epoch segment ground truth ground truth ground truth ground truth
- 36. Cycle-Shape-GAN l Cycle-Shape-GAN Cycle-GANsegmentor l