41 citations · 46 across the 4 of their papers we have counts for
5 papers
RenderFormer-V2: Neural Rendering with Heterogeneous Scene Primitives
Chong Zeng, Yue Dong, Pieter Peers +2
We present 'RenderFormer-V2', a unified learned transformer-based neural rendering model, complementary to modern physics-based rendering systems, that can handle diverse light-tra…
InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation
Yang Yue, Fangyun Wei, Tianyu He +10
Text and faces are among the most perceptually salient and practically important patterns in visual generation, yet they remain challenging for autoregressive generators built on d…
SQuadGen: Generating Simple Quad Layouts via Chart Distance Fields
Youkang Kong, Yang Liu, Yue Dong +2
3D shapes from scanning, reconstruction, or AI-generated content often lack simple quad mesh layouts -- critical for efficient editing and modeling. Existing quad-remeshing techniq…
RenderFormer: Transformer-based Neural Rendering of Triangle Meshes with Global Illumination
Chong Zeng, Yue Dong, Pieter Peers +2
We present RenderFormer, a neural rendering pipeline that directly renders an image from a triangle-based representation of a scene with full global illumination effects and that d…
DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generation
Chong Zeng, Yue Dong, Pieter Peers +3
This paper presents a novel method for exerting fine-grained lighting control during text-driven diffusion-based image generation. While existing diffusion models already have the…