16 citations · 43 across the 14 of their papers we have counts for
14 papers
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…
GeneFormer: Learned Gene Compression using Transformer-based Context Modeling
Zhanbei Cui, Yu Liao, Tongda Xu +1
With the development of gene sequencing technology, an explosive growth of gene data has been witnessed. And the storage of gene data has become an important issue. Traditional gen…
ECM-OPCC: Efficient Context Model for Octree-based Point Cloud Compression
Yiqi Jin, Ziyu Zhu, Tongda Xu +2
Recently, deep learning methods have shown promising results in point cloud compression. For octree-based point cloud compression, previous works show that the information of ances…
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…
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…
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…
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…
Bit Allocation using Optimization
Tongda Xu, Han Gao, Chenjian Gao +10
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC). First, we reveal a fundamental relationship between bit allocation in NVC and Semi-Amort…
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…
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…
Edge-enhanced Feature Distillation Network for Efficient Super-Resolution
Yan Wang
With the recently massive development in convolution neural networks, numerous lightweight CNN-based image super-resolution methods have been proposed for practical deployments on…
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…
Checkerboard Context Model for Efficient Learned Image Compression
Dailan He, Yaoyan Zheng, Baocheng Sun +2
For learned image compression, the autoregressive context model is proved effective in improving the rate-distortion (RD) performance. Because it helps remove spatial redundancies…
Cross-dataset Training for Class Increasing Object Detection
Yongqiang Yao, Yan Wang, Yu Guo +3
We present a conceptually simple, flexible and general framework for cross-dataset training in object detection. Given two or more already labeled datasets that target for differen…