collaborators

5 papers

cs.CV2026

GVCCTurbo: Rate-Compute Quality Scheduling for Codebook Driven Generative Compression

Ziyue Zeng, Dingjie Peng, Xun Su +1

Codebook-driven generative compression uses a pretrained image or video generator as a zero-shot visual prior and transmits compact codebook indices to guide reconstruction at ultr…

cs.CV2026

GVCC: Zero-Shot Video Compression via Codebook-Driven Stochastic Rectified Flow

Ziyue Zeng, Xun Su, Haoyuan Liu +3

At ultra-low bitrates, high-fidelity reconstruction requires sampling plausible videos from the posterior rather than regressing to oversmoothed conditional means. We propose Gener…

eess.IV2026

Training-Free Adaptive Quantization for Variable Rate Image Coding for Machines

Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe

Image Coding for Machines (ICM) has become increasingly important with the rapid integration of computer vision technology into real-world applications. However, most neural networ…

eess.IV2025

Explicit Residual-Based Scalable Image Coding for Humans and Machines

Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe

Scalable image compression is a technique that progressively reconstructs multiple versions of an image for different requirements. In recent years, images have increasingly been c…

cs.CV2025

Seed Selection for Human-Oriented Image Reconstruction via Guided Diffusion

Yui Tatsumi, Ziyue Zeng, Hiroshi Watanabe

Conventional methods for scalable image coding for humans and machines require the transmission of additional information to achieve scalability. A recent diffusion-based approach…