7 papers · 1 filter
FlowMotion: Training-Free Flow Guidance for Video Motion Transfer
Zhen Wang, Youcan Xu, Jun Xiao +1
Video motion transfer aims to generate a target video that inherits motion patterns from a source video while rendering new scenes. Existing training-free approaches focus on const…
Adaptive Begin-of-Video Tokens for Autoregressive Video Diffusion Models
Tianle Cheng, Zeyan Zhang, Kaifeng Gao +1
Recent advancements in diffusion-based video generation have produced impressive and high-fidelity short videos. To extend these successes to generate coherent long videos, most vi…
Ca2-VDM: Efficient Autoregressive Video Diffusion Model with Causal Generation and Cache Sharing
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +3
With the advance of diffusion models, today's video generation has achieved impressive quality. To extend the generation length and facilitate real-world applications, a majority o…
ViD-GPT: Introducing GPT-style Autoregressive Generation in Video Diffusion Models
Kaifeng Gao, Jiaxin Shi, Hanwang Zhang +2
With the advance of diffusion models, today's video generation has achieved impressive quality. But generating temporal consistent long videos is still challenging. A majority of v…
: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
Weiquan Wang, Jun Xiao, Chunping Wang +3
Continuous diffusion models have demonstrated their effectiveness in addressing the inherent uncertainty and indeterminacy in monocular 3D human pose estimation (HPE). Despite thei…
FreeTuner: Any Subject in Any Style with Training-free Diffusion
Youcan Xu, Zhen Wang, Jun Xiao +2
With the advance of diffusion models, various personalized image generation methods have been proposed. However, almost all existing work only focuses on either subject-driven or s…