142 citations · 244 across the 9 of their papers we have counts for
9 papers
A heterogeneous group CNN for image super-resolution
Chunwei Tian, Yanning Zhang, Wangmeng Zuo +3
Convolutional neural networks (CNNs) have obtained remarkable performance via deep architectures. However, these CNNs often achieve poor robustness for image super-resolution (SR)…
Image Super-resolution with An Enhanced Group Convolutional Neural Network
Chunwei Tian, Yixuan Yuan, Shichao Zhang +3
CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image supe…
Learning Context-Based Non-local Entropy Modeling for Image Compression
Mu Li, Kai Zhang, Wangmeng Zuo +2
The entropy of the codes usually serves as the rate loss in the recent learned lossy image compression methods. Precise estimation of the probabilistic distribution of the codes pl…
Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression
Mu Li, Kede Ma, Jane You +2
Precise estimation of the probabilistic structure of natural images plays an essential role in image compression. Despite the recent remarkable success of end-to-end optimized imag…
Learning Content-Weighted Deep Image Compression
Mu Li, Wangmeng Zuo, Shuhang Gu +2
Learning-based lossy image compression usually involves the joint optimization of rate-distortion performance. Most existing methods adopt spatially invariant bit length allocation…
Enlarging Context with Low Cost: Efficient Arithmetic Coding with Trimmed Convolution
Mu Li, Shuhang Gu, David Zhang +1
Arithmetic coding is an essential class of coding techniques. One key issue of arithmetic encoding method is to predict the probability of the current coding symbol from its contex…