[CVPR 2023] Executing your Commands via Motion Diffusion in Latent Space, a fast and high-quality motion diffusion model - ChenFengYe/motion-latent-diffusion
Motion Latent Diffusion Model 基本是DDPM,略。 Conditional Motion Latent Diffusion Model 这里我们引入两个具体的任务,text-to-motion和action-to-motion。对于text,我们用CLIP将其映射为embedding,对于action,我们直接学习learnable embedding即可。我们比较之后发现把embedding加到序列前比作为memory更好。我们的训练目标...
In this paper, we introduce a novel Latent Motion Diffusion model (LaMoD) to predict highly accurate DENSE motions from standard CMR videos. More specifically, our method first employs an encoder from a pre-trained registration network that learns latent motion features (also considered as ...
Through careful design, the motion-decomposed video autoencoder can compress patterns in movement into a concise latent motion representation. Consequently, the diffusion-based motion generator is able to efficiently generate realistic motion on a continuous latent space under multi-modal conditions, at ...
We proposed a novel latent motion diffusion model to estimate the motion field in the fluid regions of the generated landscape images. The input motion sketches serve as the conditions to control the generated vector fields in the masked fluid regions with the prompt. To synthesize the cinema...
但是我们后面用的text encoder是CLIP的encoder,它会把文本数据映射到另一个latent space,这两个latent space如果我们不加限制,肯定不一样,到时候transformer的decoder工作不了,所以要把text latent space和motion latent space对齐,论文里将CLIP的image latent space也对齐了,如下图所示,所以MOTION CLIP也可以实现image2...
a model that, for the first time, leverages latent diffusion models in HMP to sample from alatent spacewhere behavior is disentangled from pose and motion. As a result, diversity is encouraged from a behavioral perspective. Thanks to our behavior coupler's ability to transfer sampled behavior to...
Fi- nally, we propose several enhancements to the representa- tion, including PCA-based latent trajectory diffusion and improved trajectory sample clustering to further boost the performance of our model. In summary, the main contributions of this work are: • A...
Human behavior has the nature of indeterminacy, which requires the pedestrian trajectory prediction system to model the multi-modality of future motion states. Unlike existing stochastic trajectory prediction methods which usually use a latent variable to represent multi-modality, we explicitly simulate the...
第二种方法是特征转换式,大模型输入驱动源信号后,由大模型生成相关细粒度描述并通过Projection层生成Motion Latent特征,作为生成条件拼入扩散模型,例如InstructAvatar的方法,在此处其实还可以借助Qformer或其他映射方法使得多模态大模型直接生成动作表征。 多模态大语言模型LLMs在动作规划中的应用,带来了以下优势: >> ...