activity
20192022
most citedFlexible Neural Image Compression via Code Editing

5 citations · 9 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2022

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…

cs.CV2022

Spatial Moment Pooling Improves Neural Image Assessment

Tongda Xu, Yifan Shao, Yan Wang +1

In recent years, there has been widespread attention drawn to convolutional neural network (CNN) based blind image quality assessment (IQA). A large number of works start by extrac…

cs.CV2022

Multi-Sample Training for Neural Image Compression

Tongda Xu, Yan Wang, Dailan He +4

This paper considers the problem of lossy neural image compression (NIC). Current state-of-the-art (sota) methods adopt uniform posterior to approximate quantization noise, and sin…

eess.IV20225 cited

Flexible Neural Image Compression via Code Editing

Chenjian Gao, Tongda Xu, Dailan He +2

Neural image compression (NIC) has outperformed traditional image codecs in rate-distortion (R-D) performance. However, it usually requires a dedicated encoder-decoder pair for eac…

eess.IV2022

PO-ELIC: Perception-Oriented Efficient Learned Image Coding

Dailan He, Ziming Yang, Hongjiu Yu +7

In the past years, learned image compression (LIC) has achieved remarkable performance. The recent LIC methods outperform VVC in both PSNR and MS-SSIM. However, the low bit-rate re…

cs.CV20213 cited

HLIC: Harmonizing Optimization Metrics in Learned Image Compression by Reinforcement Learning

Baocheng Sun, Meng Gu, Dailan He +3

Learned image compression is making good progress in recent years. Peak signal-to-noise ratio (PSNR) and multi-scale structural similarity (MS-SSIM) are the two most popular evalua…