Deep Convolutional Inverse Graphics Network(DCIGN)
Deep Convolutional Inverse Graphics Network 摘要 本文介绍了深度卷积逆图形网络（DC-IGN），该模型旨在学习可解释的图像表示形式，该图像与三维场景结构、深度旋转和光照变化等视角转换解耦(disentangled)。 DC-IGN模型由多层卷积和反卷积算子组成，并使用随机梯度变化贝叶斯（SGVB）算法进行训练[10]。我们提出了一种训练程序来鼓励
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相关文章
- 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. 总结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