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…
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…
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…