3 papers
cs.CV2026
Denoising as Path Planning: Training-Free Acceleration of Diffusion Models with DPCache
Bowen Cui, Yuanbin Wang, Huajiang Xu +6
Diffusion models have demonstrated remarkable success in image and video generation, yet their practical deployment remains hindered by the substantial computational overhead of mu…
cs.CV2025
Prompt-Guided Dual Latent Steering for Inversion Problems
Yichen Wu, Xu Liu, Chenxuan Zhao +1
Inverting corrupted images into the latent space of diffusion models is challenging. Current methods, which encode an image into a single latent vector, struggle to balance structu…
cs.CV2025
Training-Free Multi-Style Fusion Through Reference-Based Adaptive Modulation
Xu Liu, Yibo Lu, Xinxian Wang +1
We propose Adaptive Multi-Style Fusion (AMSF), a reference-based training-free framework that enables controllable fusion of multiple reference styles in diffusion models. Most of…