Paper Notes
GitHub
SIGGRAPH Asia 2023 · Neural & Generative · 共 30 篇
  • A Neural Space-Time Representation for Text-to-Image Personalization
  • AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections
  • Anything to Glyph: Artistic Font Synthesis via Text-to-Image Diffusion Model
  • AvatarStudio: Text-Driven Editing of 3D Dynamic Human Head Avatars
  • Break-A-Scene: Extracting Multiple Concepts from a Single Image
  • CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape Exploration
  • Concept Decomposition for Visual Exploration and Inspiration
  • Content-based Search for Deep Generative Models
  • Diffusion-based Holistic Texture Rectification and Synthesis
  • Discontinuity-Aware 2D Neural Fields
  • Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models
  • DreamEditor: Text-Driven 3D Scene Editing with Neural Fields
  • Enhancing Diffusion Models with 3D Perspective Geometry Constraints
  • EXIM: A Hybrid Explicit-Implicit Representation for Text-Guided 3D Shape Generation
  • Face0: Instantaneously Conditioning a Text-to-Image Model on a Face
  • GroomGen: A High-Quality Generative Hair Model Using Hierarchical Latent Representations
  • HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image
  • IconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformers
  • Interactive Story Visualization with Multiple Characters
  • Learning Gradient Fields for Scalable and Generalizable Irregular Packing
  • MatFusion: A Generative Diffusion Model for SVBRDF Capture

    从搜索结果或列表筛选点进论文后，这里会显示那一批结果。

    Conference

    Anything to Glyph: Artistic Font Synthesis via Text-to-Image Diffusion Model

    Changshuo Wang, Lei Wu, Xiaole Liu, Xiang Li, Lei Meng, Xiangxu Meng

    Shandong University

    SIGGRAPH Asia 2023Neural & GenerativeArtistic Font SynthesisDiffusion ModelText-to-ImageGlyph GenerationFont Generation
    Paper
    This note has no summary yet.