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TYPO in Algorithm 1.
reshape_featrue -> reshape_feature
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arxiv:2405.01434
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
Published on May 2, 2024
Abstract
StoryDiffusion, combining consistent self-attention and semantic motion prediction, enables generation of coherent and stable images and videos from textual descriptions.
AI-generated summary
For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents a significant challenge. In this paper, we propose a new way of self-attention calculation, termed Consistent Self-Attention, that significantly boosts the consistency between the generated images and augments prevalent pretrained diffusion-based text-to-image models in a zero-shot manner. To extend our method to long-range video generation, we further introduce a novel semantic space temporal motion prediction module, named Semantic Motion Predictor. It is trained to estimate the motion conditions between two provided images in the semantic spaces. This module converts the generated sequence of images into videos with smooth transitions and consistent subjects that are significantly more stable than the modules based on latent spaces only, especially in the context of long video generation. By merging these two novel components, our framework, referred to as StoryDiffusion, can describe a text-based story with consistent images or videos encompassing a rich variety of contents. The proposed StoryDiffusion encompasses pioneering explorations in visual story generation with the presentation of images and videos, which we hope could inspire more research from the aspect of architectural modifications. Our code is made publicly available at https://github.com/HVision-NKU/StoryDiffusion.
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TYPO in Algorithm 1.
reshape_featrue -> reshape_feature
This is an automated message from the Librarian Bot. I found the following papers similar to this paper.
The following papers were recommended by the Semantic Scholar API
- Tuning-Free Noise Rectification for High Fidelity Image-to-Video Generation (2024)
- From Parts to Whole: A Unified Reference Framework for Controllable Human Image Generation (2024)
- OneActor: Consistent Character Generation via Cluster-Conditioned Guidance (2024)
- Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition (2024)
- PoseAnimate: Zero-shot high fidelity pose controllable character animation (2024)
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