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pengxiang/TrackDiffusion_SVD_Stage2
TrackDiffusion_SVD_Stage2 is a text-to-video model from pengxiang. Use it when you need video from a text prompt. The card lists the license as other.
Please download the weights from this link(https://huggingface.co/pengxiang/trackdiffusionytvis). TrackDiffusion is a diffusion model that takes in tracklets as conditions, and generates a video from it.
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Updated Jan 9, 2025
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From the Hugging Face model README
Please download the weights from this link(https://huggingface.co/pengxiang/trackdiffusion_ytvis).
<!-- Provide a quick summary of what the model is/does. -->TrackDiffusion is a diffusion model that takes in tracklets as conditions, and generates a video from it.
TrackDiffusion is a novel video generation framework that enables fine-grained control over complex dynamics in video synthesis by conditioning the generation process on object trajectories. This approach allows for precise manipulation of object trajectories and interactions, addressing the challenges of managing appearance, disappearance, scale changes, and ensuring consistency across frames.
We provide the weights for the entire unet, so you can replace it in diffusers pipeline, for example:
pretrained_model_path = "stabilityai/stable-video-diffusion-img2vid"
unet = UNetSpatioTemporalConditionModel.from_pretrained("/path/to/unet", torch_dtype=torch.float16,)
pipe = StableVideoDiffusionPipeline.from_pretrained(
pretrained_model_path,
unet=unet,
torch_dtype=torch.float16,
variant="fp16",
low_cpu_mem_usage=True)