9 citations · 9 across the 6 of their papers we have counts for
10 papers
WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA
Zhihao Zhu, Hanlin Shang, Mingwang Xu +6
Vision-Language-Action (VLA) models have emerged as a prominent paradigm for end-to-end autonomous driving; however, their efficient deployment is severely constrained by high comp…
EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation
Cong Wang, Jiaxi Gu, Panwen Hu +5
Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. Ho…
Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution
Qingping Zheng, Ling Zheng, Yuanfan Guo +4
Artifact-free super-resolution (SR) aims to translate low-resolution images into their high-resolution counterparts with a strict integrity of the original content, eliminating any…
PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion
Guansong Lu, Yuanfan Guo, Jianhua Han +7
Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However,…
DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
Cong Wang, Jiaxi Gu, Panwen Hu +3
Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided i…
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models
Fengyuan Shi, Jiaxi Gu, Hang Xu +3
Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthes…