4 papers · 1 filter
RGBX-Next: Towards Realistic Generative Rendering from G-Buffers
Zheng Zeng, Marco Salvi, Lifan Wu +9
Diffusion models have achieved impressive results in image, video, and streaming generation. However, compared to traditional 3D rendering, they still lack precise control over the…
VideoNeuMat: Neural Material Extraction from Generative Video Models
Bowen Xue, Saeed Hadadan, Zheng Zeng +3
Creating photorealistic materials for 3D rendering requires exceptional artistic skill. Generative models for materials could help, but are currently limited by the lack of high-qu…
GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering
Jiaye Wu, Saeed Hadadan, Geng Lin +3
In this paper, we present GaNI, a Global and Near-field Illumination-aware neural inverse rendering technique that can reconstruct geometry, albedo, and roughness parameters from i…
GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera
Jiaye Wu, Saeed Hadadan, Geng Lin +4
Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among multiple objects. While natural…