Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracing
Author:
Affiliation:
1. State Key Laboratory of CAD&CG, Zhejiang University, China
2. Adobe Research, United States of America
3. State Key Laboratory of CAD&CG, Zhejiang University, China and Zhejiang Lab, China
4. KooLab, Manycore, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3550469.3555407
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1. Neural Point-Based Graphics
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3. Intrinsic images in the wild
4. Material recognition in the wild with the Materials in Context Database
5. Matterport3D: Learning from RGB-D Data in Indoor Environments
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2. I2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06
3. MAIR: Multi-View Attention Inverse Rendering with 3D Spatially-Varying Lighting Estimation;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06
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