Anle Ke — accepted AI-conference papers

2026

DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression

Junqi Shi, Ming Lu, Xingchen Li, Anle Ke, Ruiqi Zhang, Zhan Ma

CVPR 2026

Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage.Most existing diffusion codecs employ UNet architectures, where hierarchical downsampling forces diffusion to operate in shall

Cited by 0 Source ↗code ↗Scholar ↗

2025

Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion

Anle Ke, Xu Zhang, Tong Chen, Ming Lu, Chao Zhou, Jiawen Gu +1

ICML 2025poster

Existing multimodal large model-based image compression frameworks often rely on a fragmented integration of semantic retrieval, latent compression, and generative models, resulting in suboptimal performance in both reconstruction fidelity and coding efficiency. To address these challenges, we propo…

Cited by 0 Source ↗PDF ↗Scholar ↗