Deep Convolutional Inverse Graphics Network(DCIGN)
Deep Convolutional Inverse Graphics Network 摘要 本文介紹了深度卷積逆圖形網絡（DC-IGN），該模型旨在學習可解釋的圖像表示形式，該圖像與三維場景結構、深度旋轉和光照變化等視角轉換解耦(disentangled)。 DC-IGN模型由多層卷積和反捲積算子組成，並使用隨機梯度變化貝葉斯（SGVB）算法進行訓練[10]。我們提出了一種訓練程序來鼓勵
相關文章
- 1. Convolutional Neural Networks----Deep Convolutional Models:case studies
- 2. Deep Graph-Convolutional Image Denoising
- 3. Deep Clustering with Convolutional Autoencoders
- 4. Deep Convolutional Neural Network Architecture
- 5. 015 Deep convolutional models:case studies
- 6. 總結Deep Convolutional Neural Network for Image Deconvolution
- 7. ImageNet Classification with Deep Convolutional Neural Networks
- 8. Very Deep Convolutional Networks for Text Classification
- 9. 《ImageNet Classification with Deep Convolutional Neural Network》
- 10. AlexNet：ImageNet Classification with Deep Convolutional Neural Networks
- 更多相關文章...
- • R 包 - R 語言教程
- • Hibernate的級聯與反轉 - Hibernate教程
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Convolutional Neural Networks----Deep Convolutional Models:case studies
- 2. Deep Graph-Convolutional Image Denoising
- 3. Deep Clustering with Convolutional Autoencoders
- 4. Deep Convolutional Neural Network Architecture
- 5. 015 Deep convolutional models:case studies
- 6. 總結Deep Convolutional Neural Network for Image Deconvolution
- 7. ImageNet Classification with Deep Convolutional Neural Networks
- 8. Very Deep Convolutional Networks for Text Classification
- 9. 《ImageNet Classification with Deep Convolutional Neural Network》
- 10. AlexNet：ImageNet Classification with Deep Convolutional Neural Networks