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SIGGRAPH Asia 2024 · Neural & Generative · 共 50 篇
  • L3DG: Latent 3D Gaussian Diffusion
  • LLM-enhanced Scene Graph Learning for Household Rearrangement
  • Lumiere: A Space-Time Diffusion Model for Video Generation
  • LVCD: Reference-based Lineart Video Colorization with Diffusion Models
  • MagicClay: Sculpting Meshes With Generative Neural Fields
  • MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation
  • MV2MV: Multi-View Image Translation via View-Consistent Diffusion Models
  • Neural Differential Appearance Equations
  • PALP: Prompt Aligned Personalization of Text-to-Image Models
  • Portrait Video Editing Empowered by Multimodal Generative Priors
  • Procedural Material Generation with Reinforcement Learning
  • ProcessPainter: Learning to draw from sequence data
  • ReVersion: Diffusion-Based Relation Inversion from Images
  • SD-πXL: Generating Low-Resolution Quantized Imagery via Score Distillation
  • SGEdit: Bridging LLM with Text2Image Generative Model for Scene Graph-based Image Editing
  • Still-Moving: Customized Video Generation without Customized Video Data
  • Style-NeRF2NeRF: 3D Style Transfer from Style-Aligned Multi-View Images
  • StyleCrafter: Taming Artistic Video Diffusion with Reference-Augmented Adapter Learning
  • StyleTex: Style Image-Guided Texture Generation for 3D Models
  • TALK-Act: Enhance Textural-Awareness for 2D Speaking Avatar Reenactment with Diffusion Model
  • TEXGen: a Generative Diffusion Model for Mesh Textures

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    Journal

    Procedural Material Generation with Reinforcement Learning

    Beichen Li, Yiwei Hu, Paul Guerrero, Milos Hasan, Liang Shi, Valentin Deschaintre, Wojciech Matusik

    MIT; Adobe

    SIGGRAPH Asia 2024Neural & Generative
    Procedural MaterialReinforcement LearningTransformerMaterial GraphGenerative Model
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