Our study introduces a new image-to-video generator called FashionFlow. By
utilising a diffusion model, we are able to create short videos from still
images. Our approach involves developing and connecting relevant components
with the diffusion model, which sets our work apart. The components include the
use of pseudo-3D convolutional layers to generate videos efficiently. VAE and
CLIP encoders capture vital characteristics from still images to influence the
diffusion model. Our research demonstrates a successful synthesis of fashion
videos featuring models posing from various angles, showcasing the fit and
appearance of the garment. Our findings hold great promise for improving and
enhancing the shopping experience for the online fashion industry.

我们的研究介绍了一种名为 FashionFlow 的新型图像 - 视频生成器。通过利用扩散模型，我们能够从静止图像中创建短视频。我们的方法涉及开发和连接与扩散模型相关的组件，这使得我们的工作与众不同。这些组件包括使用伪 3D 卷积层高效生成视频。VAE 和 CLIP 编码器从静止图像中捕获重要特征以影响扩散模型。我们的研究展示了成功合成时尚视频，展示了模特从多个角度展示服装的合身和外观。我们的发现对于改进和提升在线时尚行业的购物体验具有巨大潜力。