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Found 4 papers, 3 papers with code
CGB-DM: Content and Graphic Balance Layout Generation with Transformer-based Diffusion Model
We find that these methods overly focus on content information and lack constraints on layout spatial structure, resulting in an imbalance of learning content-aware and graphic-aware features.
ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generation
We introduce a new benchmark, ChartMimic, aimed at assessing the visually-grounded code generation capabilities of large multimodal models (LMMs).
StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style Adapter
To address these challenges, we introduce StyleCrafter, a generic method that enhances pre-trained T2V models with a style control adapter, enabling video generation in any style by providing a reference image.
Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
To derive the transitional state during the forward process, we introduce Distortion Adaptive Inversion.
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