[图像超分]--Adaptive Densely Connected Single Image Super-Resolution
点评一下，如有不对的地方，请联系更正！首先本文的实验结果非常优秀，超越了RCAN、SAN等方法，但是也隐藏了几个不公平的trick，例如：1.网络通道数是128，RCAN、SAN均为64通道；2.训练数据集为DIV2K+Flickr2K共3000多张图片，RCAN、SAN等只采用DIV2K800张图片训练。此外感觉论文的消融实验分析缺少了个整个网络整体各个模块的贡献度，仅仅是拿出来单独测试了一下有
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相关文章
- 1. Densely Connected Convolutional Networks
- 2. Densely Connected Convolutional Networks(DenseNet)
- 3. DenseNet: Densely connected convolutional network
- 4. Densely Connected Convolutional Networks (DenseNet 2017 CVPR)
- 5. 【图像超分辨】Densely Residual Laplacian Super-Resolution
- 6. Densely Connected Convolutional Networks(2017)
- 7. DenseNet Densely Connected Convolutional Networks
- 8. DenseNet——Densely Connected Convolutional Networks
- 9. 真实噪声：Densely Connected Hierarchical Network for Image Denoising（CVPRW2019） 阅读理解
- 10. DenseNet---《Densely Connected Convolutional Networks》