1 citations · 2 across the 13 of their papers we have counts for
15 papers
DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression
Junqi Shi, Ming Lu, Xingchen Li +3
Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage. Most…
Reinforced Rate Control for Neural Video Compression via Inter-Frame Rate-Distortion Awareness
Wuyang Cong, Junqi Shi, Lizhong Wang +4
Neural video compression (NVC) has demonstrated superior compression efficiency, yet effective rate control remains a significant challenge due to complex temporal dependencies. Ex…
ResTok: Learning Hierarchical Residuals in 1D Visual Tokenizers for Autoregressive Image Generation
Xu Zhang, Cheng Da, Huan Yang +3
Existing 1D visual tokenizers for autoregressive (AR) generation largely follow the design principles of language modeling, as they are built directly upon transformers whose prior…
YODA: Yet Another One-step Diffusion-based Video Compressor
Xingchen Li, Junzhe Zhang, Junqi Shi +2
While one-step diffusion models have recently excelled in perceptual image compression, their application to video remains limited. Prior efforts typically rely on pretrained 2D au…
Neural B-frame Video Compression with Bi-directional Reference Harmonization
Yuxi Liu, Dengchao Jin, Shuai Huo +5
Neural video compression (NVC) has made significant progress in recent years, while neural B-frame video compression (NBVC) remains underexplored compared to P-frame compression. N…
Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic Inference
Xu Zhang, Ming Lu, Yan Chen +1
In recent years, compressed domain semantic inference has primarily relied on learned image coding models optimized for mean squared error (MSE). However, MSE-oriented optimization…
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen +4
Existing multimodal large model-based image compression frameworks often rely on a fragmented integration of semantic retrieval, latent compression, and generative models, resultin…
DreamInsert: Zero-Shot Image-to-Video Object Insertion from A Single Image
Qi Zhao, Zhan Ma, Pan Zhou
Recent developments in generative diffusion models have turned many dreams into realities. For video object insertion, existing methods typically require additional information, su…
Towards Loss-Resilient Image Coding for Unstable Satellite Networks
Hongwei Sha, Muchen Dong, Quanyou Luo +3
Geostationary Earth Orbit (GEO) satellite communication demonstrates significant advantages in emergency short burst data services. However, unstable satellite networks, particular…
High-Efficiency Neural Video Compression via Hierarchical Predictive Learning
Ming Lu, Zhihao Duan, Wuyang Cong +3
The enhanced Deep Hierarchical Video Compression-DHVC 2.0-has been introduced. This single-model neural video codec operates across a broad range of bitrates, delivering not only s…
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation
Xu Zhang, Peiyao Guo, Ming Lu +1
Image coding for multi-task applications, catering to both human perception and machine vision, has been extensively investigated. Existing methods often rely on multiple task-spec…
Accelerating block-level rate control for learned image compression
Muchen Dong, Ming Lu, Zhan Ma
Despite the unprecedented compression efficiency achieved by deep learned image compression (LIC), existing methods usually approximate the desired bitrate by adjusting a single qu…
Towards Backward-Compatible Continual Learning of Image Compression
Zhihao Duan, Ming Lu, Justin Yang +3
This paper explores the possibility of extending the capability of pre-trained neural image compressors (e.g., adapting to new data or target bitrates) without breaking backward co…
Another Way to the Top: Exploit Contextual Clustering in Learned Image Coding
Yichi Zhang, Zhihao Duan, Ming Lu +3
While convolution and self-attention are extensively used in learned image compression (LIC) for transform coding, this paper proposes an alternative called Contextual Clustering b…
Deep Hierarchical Video Compression
Ming Lu, Zhihao Duan, Fengqing Zhu +1
Recently, probabilistic predictive coding that directly models the conditional distribution of latent features across successive frames for temporal redundancy removal has yielded…