ViStoryBench: Comprehensive Benchmark Suite for Story Visualization
원문 초록
Story visualization, which aims to generate a sequence of visually coherent images aligning with a given narrative and reference images, has seen significant progress with recent advancements in generative models. To further enhance the performance of story visualization frameworks in real-world scenarios, we introduce a comprehensive evaluation benchmark, ViStoryBench. We collect a diverse dataset encompassing various story types and artistic styles, ensuring models are evaluated across multiple dimensions such as different plots (e.g., comedy, horror) and visual aesthetics (e.g., anime, 3D renderings). ViStoryBench is carefully curated to balance narrative structures and visual elements, featuring stories with single and multiple protagonists to test models' ability to maintain character consistency. Additionally, it includes complex plots and intricate world-building to challenge models in generating accurate visuals. To ensure comprehensive comparisons, our benchmark incorporates a wide range of evaluation metrics assessing critical aspects. This structured and multifaceted framework enables researchers to thoroughly identify both the strengths and weaknesses of different models, fostering targeted improvements.
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Consistent Story Generation with Asymmetry Zigzag Sampling
StoryWeaver: A Unified World Model for Knowledge-Enhanced Story Character Customization
ContextualStory: Consistent Visual Storytelling with Spatially-Enhanced and Storyline Context
Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models
StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion
Masked Generative Story Transformer with Character Guidance and Caption Augmentation
토론
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