Pose Guided Person Image Generation
生成網絡 網絡包含兩個生成網絡,分別爲G1,G2. 生成網絡G1輸入爲condition image和target pos的串聯,生成粗略的姿勢圖像,即coarse result. 生成網絡G2,將condition image,與生成網絡G1的輸入串聯,輸入G2,生成一個difference map. 將G1,G2生成圖像相加得到最後的生成圖像,即refined result. 判別網絡 判別網
相關文章
- 1. Pose-Normalized Image Generation for Person Re-identification (note)
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- 3. CVPR2018：Disentangled Person Image Generation 換裝換姿勢
- 4. Multi person-pose estimation
- 5. 行人重識別（Person Re-ID）【五】：論文筆記——Pose-Normalized Image Generation for Person Re-identification
- 6. Pose-guided Visible Part Matching for Occluded Person ReID閱讀筆記
- 7. Pose-Guided Feature Alignment for Occluded Person Re-Identification閱讀筆記
- 8. Attribute-Guided Face Generation Using Conditional CycleGAN
- 9. Guided Image Filtering
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相關文章
- 1. Pose-Normalized Image Generation for Person Re-identification (note)
- 2. Pose-Normalized Image Generation for Person Re-identification 論文筆記
- 3. CVPR2018：Disentangled Person Image Generation 換裝換姿勢
- 4. Multi person-pose estimation
- 5. 行人重識別（Person Re-ID）【五】：論文筆記——Pose-Normalized Image Generation for Person Re-identification
- 6. Pose-guided Visible Part Matching for Occluded Person ReID閱讀筆記
- 7. Pose-Guided Feature Alignment for Occluded Person Re-Identification閱讀筆記
- 8. Attribute-Guided Face Generation Using Conditional CycleGAN
- 9. Guided Image Filtering
- 10. MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network