Yiwei Hu

Yiwei Hu

Research Scientist

Adobe Research

Biography

I am a research scientist at Adobe Research. I received my Ph.D. from Yale University, under the supervision by Prof. Holly Rushmeier and Prof. Julie Dorsey. Prior to Yale, I received my bachelor’s degree from Zhejiang University, advised by Prof. Rui Wang.

My research focuses on 2D and 3D graphics, with a special interest in generative AI for content creation at Adobe. We shipped multiple GenAI 2D/3D workflows in Substance 3D Viewer, Substance 3D Stager and Substance 3D API as Firefly Service involving generative asset creation and composition etc. I am exploring more interesting multi-modality content creation methods, models and workflows. I am open to collaborations and welcome strong Ph.D. students interested in research internships at Adobe Research.

Interests
  • Computer Graphics
  • Computer Vision
  • Artificial Intelligence
Education
  • PhD in Computer Graphics, 2023

    Yale University

  • BSc in Computer Science, 2018

    Zhejiang University

Publications

(2025). OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions. NeurIPS 2025.

Project

(2025). AniTex: light-geometry consistent PBR Material Generation for Animatable Objects. SIGGRAPH ASIA 2025.

(2025). Generating 360 Video is What You Need For a 3D Scene. SIGGRAPH ASIA 2025.

Project

(2025). MaterialPicker: Multi-Modal DiT-Based Material Generation. ACM Transactions on Graphics (SIGGRAPH 2025).

Project

(2025). Buffer Anytime: Zero-Shot Video Depth and Normal from Image Priors. CVPR 2025.

PDF Project

(2025). Turbo3D: Ultra-fast Text-to-3D Generation. CVPR 2025.

PDF Project

(2025). RelitLRM: Generative Relightable Radiance for Large Reconstruction Models. ICLR 2025.

PDF Project

(2024). Procedural Material Generation with Reinforcement Learning. ACM Transactions on Graphics (SIGGRAPH ASIA 2024).

PDF Code DOI

(2024). TexSliders: Diffusion-Based Texture Editing in CLIP Space. SIGGRAPH 2024.

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(2024). RGB↔X: Image Decomposition and Synthesis Using Material- and Lighting-aware Diffusion Models. SIGGRAPH 2024.

PDF Project

(2023). Generating Procedural Materials from Text or Image Prompts. SIGGRAPH 2023.

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(2022). Multirate Shading with Piecewise Interpolatory Approximation. Computer Graphics Forum, Proc. of Pacific Graphics (PG 2022).

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(2022). Node Graph Optimization Using Differentiable Proxies. SIGGRAPH 2022.

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(2022). Controlling Material Appearance by Examples. Computer Graphics Forum, Proc. of Eurographics Symposium on Rendering (EGSR 2022).

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(2022). An Inverse Procedural Modeling Pipeline for SVBRDF Maps. ACM Transactions on Graphics (Presented at SIGGRAPH 2022).

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(2019). A Novel Framework for Inverse Procedural Texture Modeling. ACM Transactions on Graphics (SIGGRAPH ASIA 2019).

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(2019). Novel Radiomic Features Based on Graph Theory for PET Image Analysis. IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

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