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SIGGRAPH 2025 · Neural & Generative · 共 48 篇
  • IntrinsicEdit: Precise generative image manipulation in intrinsic space
  • IP-Composer: Semantic Composition of Visual Concepts
  • IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual Prompting
  • LayerPano3D: Layered 3D Panorama for Hyper-Immersive Scene Generation
  • MaterialPicker: Multi-Modal DiT-Based Material Generation
  • MIND: Microstructure INverse Design with Generative Hybrid Neural Representation
  • MotionCanvas: Cinematic Shot Design with Controllable Image-to-Video Generation
  • MyTimeMachine: Personalized Facial Age Transformation
  • Nested Attention: Semantic-aware Attention Values for Concept Personalization
  • OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation
  • Order Matters: Learning Element Ordering for Graphic Design Generation
  • PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models
  • pOps: Photo-Inspired Diffusion Operators
  • PrimitiveAnything: Human-Crafted 3D Primitive Assembly Generation with Auto-Regressive Transformer
  • RELATE3D: REfocusing Latent Adapter for Targeted local Enhancement and Editing in 3D Generation
  • Scene-Level Appearance Transfer with Semantic Correspondences
  • Splat4D: Diffusion-Enhanced 4D Gaussian Splatting for Temporally and Spatially Consistent Content Creation
  • StableMakeup: When Real-World Makeup Transfer Meets Diffusion Model
  • Stitch-A-Shape: Bottom-up Learning for B-Rep Generation
  • Stochastic Preconditioning for Neural Field Optimization
  • Style Customization of Text-to-Vector Generation with Image Diffusion Priors

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    Journal

    Order Matters: Learning Element Ordering for Graphic Design Generation

    Bo Yang, Ying Cao

    ShanghaiTech University

    SIGGRAPH 2025Neural & Generative
    Graphic DesignGenerative ModelElement OrderingAutoregressive ModelLayout Generation
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