4 papers
Arbitrary Ratio Feature Compression via Next Token Prediction
Yufan Liu, Daoyuan Ren, Zhipeng Zhang +4
Feature compression is increasingly important for improving the efficiency of downstream tasks, especially in applications involving large-scale or multi-modal data. While existing…
Reversing Flow for Image Restoration
Haina Qin, Wenyang Luo, Libin Wang +5
Image restoration aims to recover high-quality (HQ) images from degraded low-quality (LQ) ones by reversing the effects of degradation. Existing generative models for image restora…
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
Wenyang Luo, Haina Qin, Zewen Chen +6
Image restoration tasks like deblurring, denoising, and dehazing usually need distinct models for each degradation type, restricting their generalization in real-world scenarios wi…
Token Caching for Diffusion Transformer Acceleration
Jinming Lou, Wenyang Luo, Yufan Liu +5
Diffusion transformers have gained substantial interest in diffusion generative modeling due to their outstanding performance. However, their computational demands, particularly th…