5 papers
Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression
Shiyin Jiang, Wei Long, Minghao Han +3
The rapid growth of visual data under stringent storage and bandwidth constraints makes extremely low-bitrate image compression increasingly important. While Vector Quantization (V…
Generative Image Compression by Estimating Gradients of the Rate-variable Feature Distribution
Minghao Han, Weiyi You, Jinhua Zhang +3
While learned image compression (LIC) focuses on efficient data transmission, generative image compression (GIC) extends this framework by integrating generative modeling to produc…
Hierarchical Semantic Compression for Consistent Image Semantic Restoration
Shengxi Li, Zifu Zhang, Mai Xu +3
The emerging semantic compression has been receiving increasing research efforts most recently, capable of achieving high fidelity restoration during compression, even at extremely…
Continuous Patch Stitching for Block-wise Image Compression
Zifu Zhang, Shengxi Li, Henan Liu +2
Most recently, learned image compression methods have outpaced traditional hand-crafted standard codecs. However, their inference typically requires to input the whole image at the…
Causal Context Adjustment Loss for Learned Image Compression
Minghao Han, Shiyin Jiang, Shengxi Li +4
In recent years, learned image compression (LIC) technologies have surpassed conventional methods notably in terms of rate-distortion (RD) performance. Most present learned techniq…