12 papers
Next-Frame Decoding for Ultra-Low-Bitrate Image Compression with Video Diffusion Priors
Yunuo Chen, Chuqin Zhou, Jiangchuan Li +5
We present a novel paradigm for ultra-low-bitrate image compression (ULB-IC) that exploits the ``temporal'' evolution in generative image compression. Specifically, we define an ex…
Inevitable Encounters: Backdoor Attacks Involving Lossy Compression
Qian Li, Yunuo Chen, Yuntian Chen
Real-world backdoor attacks often require poisoned datasets to be stored and transmitted before being used to compromise deep learning systems. However, in the era of big data, the…
Adaptive Learned Image Compression with Graph Neural Networks
Yunuo Chen, Bing He, Zezheng Lyu +4
Efficient image compression relies on modeling both local and global redundancy. Most state-of-the-art (SOTA) learned image compression (LIC) methods are based on CNNs or Transform…
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…
Free-GVC: Towards Training-Free Extreme Generative Video Compression with Temporal Coherence
Xiaoyue Ling, Chuqin Zhou, Chunyi Li +4
Building on recent advances in video generation, generative video compression has emerged as a new paradigm for achieving visually pleasing reconstructions. However, existing metho…
Dual-Representation Image Compression at Ultra-Low Bitrates via Explicit Semantics and Implicit Textures
Chuqin Zhou, Xiaoyue Ling, Yunuo Chen +3
While recent neural codecs achieve strong performance at low bitrates when optimized for perceptual quality, their effectiveness deteriorates significantly under ultra-low bitrate…