12 citations · 14 across the 9 of their papers we have counts for
9 papers
Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers
Tongda Xu, Ziran Zhu, Jian Li +8
Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution , with a predefined diffusion model , an operator , and a m…
Idempotence and Perceptual Image Compression
Tongda Xu, Ziran Zhu, Dailan He +8
Idempotence is the stability of image codec to re-compression. At the first glance, it is unrelated to perceptual image compression. However, we find that theoretically: 1) Conditi…
Unified learning-based lossy and lossless JPEG recompression
Jianghui Zhang, Yuanyuan Wang, Lina Guo +5
JPEG is still the most widely used image compression algorithm. Most image compression algorithms only consider uncompressed original image, while ignoring a large number of alread…
Bandwidth-efficient Inference for Neural Image Compression
Shanzhi Yin, Tongda Xu, Yongsheng Liang +4
With neural networks growing deeper and feature maps growing larger, limited communication bandwidth with external memory (or DRAM) and power constraints become a bottleneck in imp…
Efficient Learned Lossless JPEG Recompression
Lina Guo, Yuanyuan Wang, Tongda Xu +6
JPEG is one of the most popular image compression methods. It is beneficial to compress those existing JPEG files without introducing additional distortion. In this paper, we propo…
Conditional Perceptual Quality Preserving Image Compression
Tongda Xu, Qian Zhang, Yanghao Li +7
We propose conditional perceptual quality, an extension of the perceptual quality defined in \citet{blau2018perception}, by conditioning it on user defined information. Specificall…
Correcting the Sub-optimal Bit Allocation
Tongda Xu, Han Gao, Yuanyuan Wang +4
In this paper, we investigate the problem of bit allocation in Neural Video Compression (NVC). First, we reveal that a recent bit allocation approach claimed to be optimal is, in f…
Evaluating the Practicality of Learned Image Compression
Hongjiu Yu, Qiancheng Sun, Jin Hu +9
Learned image compression has achieved extraordinary rate-distortion performance in PSNR and MS-SSIM compared to traditional methods. However, it suffers from intensive computation…
Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain
Lina Guo, Xinjie Shi, Dailan He +4
JPEG is a popular image compression method widely used by individuals, data center, cloud storage and network filesystems. However, most recent progress on image compression mainly…