2 citations · 5 across the 13 of their papers we have counts for
16 papers
Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors
Yunuo Chen, Jingnan Gao, Bing He +6
Pretrained diffusion models provide powerful generative priors for extreme image compression, but their stochastic, iterative generation processes are not designed to decode compre…
Compressing 3D Gaussian Splatting via Cross-Representation Priors
Yezheng Zhang, Huanxiong Liang, Chuqin Zhou +2
3D Gaussian Splatting (3DGS) enables high-quality novel view synthesis but incurs high storage and transmission costs due to dense Gaussian primitives. Recent anchor-based compress…
JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications
Tong Wu, Zhiyong Chen, Guo Lu +4
Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distor…
A Multi-Grid Implicit Neural Representation for Multi-View Videos
Qingyue Ling, Zhengxue Cheng, Donghui Feng +6
Multi-view videos are becoming widely used in different fields, but their high resolution and multi-camera shooting raise significant challenges for storage and transmission. In th…
Content-Aware Mamba for Learned Image Compression
Yunuo Chen, Zezheng Lyu, Bing He +6
Recent learned image compression (LIC) leverages Mamba-style state-space models (SSMs) for global receptive fields with linear complexity. However, the standard Mamba adopts conten…
S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression
Yunuo Chen, Qian Li, Bing He +6
Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of…
Linear Attention Modeling for Learned Image Compression
Donghui Feng, Zhengxue Cheng, Shen Wang +4
Recent years, learned image compression has made tremendous progress to achieve impressive coding efficiency. Its coding gain mainly comes from non-linear neural network-based tran…
Large Language Model for Lossless Image Compression with Visual Prompts
Junhao Du, Chuqin Zhou, Ning Cao +6
Recent advancements in deep learning have driven significant progress in lossless image compression. With the emergence of Large Language Models (LLMs), preliminary attempts have b…
L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression
Junxuan Zhang, Zhengxue Cheng, Yan Zhao +4
Learning-based probabilistic models can be combined with an entropy coder for data compression. However, due to the high complexity of learning-based models, their practical applic…
AsymLLIC: Asymmetric Lightweight Learned Image Compression
Shen Wang, Zhengxue Cheng, Donghui Feng +3
Learned image compression (LIC) methods often employ symmetrical encoder and decoder architectures, evitably increasing decoding time. However, practical scenarios demand an asymme…
Controllable Distortion-Perception Tradeoff Through Latent Diffusion for Neural Image Compression
Chuqin Zhou, Guo Lu, Jiangchuan Li +4
Neural image compression often faces a challenging trade-off among rate, distortion and perception. While most existing methods typically focus on either achieving high pixel-level…
Rate-aware Compression for NeRF-based Volumetric Video
Zhiyu Zhang, Guo Lu, Huanxiong Liang +3
The neural radiance fields (NeRF) have advanced the development of 3D volumetric video technology, but the large data volumes they involve pose significant challenges for storage a…
Content-Adaptive Rate-Quality Curve Prediction Model in Media Processing System
Shibo Yin, Zhiyu Zhang, Peirong Ning +4
In streaming media services, video transcoding is a common practice to alleviate bandwidth demands. Unfortunately, traditional methods employing a uniform rate factor (RF) across a…
H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting
Bing He, Yunuo Chen, Guo Lu +5
Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time render…
Efficient Dynamic-NeRF Based Volumetric Video Coding with Rate Distortion Optimization
Zhiyu Zhang, Guo Lu, Huanxiong Liang +3
Volumetric videos, benefiting from immersive 3D realism and interactivity, hold vast potential for various applications, while the tremendous data volume poses significant challeng…
Implicit-explicit Integrated Representations for Multi-view Video Compression
Chen Zhu, Guo Lu, Bing He +2
With the increasing consumption of 3D displays and virtual reality, multi-view video has become a promising format. However, its high resolution and multi-camera shooting result in…