89 citations · 110 across the 8 of their papers we have counts for
6 papers · 1 filter
Toward Richer Material Generation via Procedural Data Enhancement
Yunchen Yu, Jacob Munkberg, Jon Hasselgren +3
Generative models for material creation are fundamentally limited by the quality and expressivity of available training data. Simple physically based rendering (PBR) materials, whi…
AlbedoEdit: Unified Instance-Level Video Editing with Albedo Guidance
Xilong Zhou, Bao-Huy Nguyen, Zheng Zeng +6
Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative downstream applications requir…
VideoMat: Extracting PBR Materials from Video Diffusion Models
Jacob Munkberg, Zian Wang, Ruofan Liang +2
We leverage finetuned video diffusion models, intrinsic decomposition of videos, and physically-based differentiable rendering to generate high quality materials for 3D models give…
Generative Detail Enhancement for Physically Based Materials
Saeed Hadadan, Benedikt Bitterli, Tizian Zeltner +6
We present a tool for enhancing the detail of physically based materials using an off-the-shelf diffusion model and inverse rendering. Our goal is to enhance the visual fidelity of…
Flexible Isosurface Extraction for Gradient-Based Mesh Optimization
Tianchang Shen, Jacob Munkberg, Jon Hasselgren +7
This work considers gradient-based mesh optimization, where we iteratively optimize for a 3D surface mesh by representing it as the isosurface of a scalar field, an increasingly co…
Appearance-Driven Automatic 3D Model Simplification
Jon Hasselgren, Jacob Munkberg, Jaakko Lehtinen +2
We present a suite of techniques for jointly optimizing triangle meshes and shading models to match the appearance of reference scenes. This capability has a number of uses, includ…