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Accelerating Hair Rendering by Learning High-Order Scattered Radiance.

, , , , , , , and . Comput. Graph. Forum, 42 (4): i-x (July 2023)

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Human Hair Inverse Rendering using Multi-View Photometric data., , , , and . EGSR (DL), page 179-190. Eurographics Association, (2021)Multispectral Photometric Stereo for Acquiring High-Fidelity Surface Normals., and . IEEE Computer Graphics and Applications, 34 (6): 57-68 (2014)HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capture., , , , , , and . CVPR, page 6133-6144. IEEE, (2022)A Local Appearance Model for Volumetric Capture of Diverse Hairstyles., , , , , , and . 3DV, page 190-200. IEEE, (2024)Accelerating Hair Rendering by Learning High-Order Scattered Radiance., , , , , , , and . Comput. Graph. Forum, 42 (4): i-x (July 2023)Practical SVBRDF acquisition of 3D objects with unstructured flash photography., , , and . ACM Trans. Graph., 37 (6): 267 (2018)NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation., , , , , , , , and . CVPR, page 8641-8651. IEEE, (2023)CT2Hair: High-Fidelity 3D Hair Modeling using Computed Tomography., , , , , , , and . ACM Trans. Graph., 42 (4): 75:1-75:13 (August 2023)Strand-Accurate Multi-View Hair Capture., , , and . CVPR, page 155-164. Computer Vision Foundation / IEEE, (2019)Neural Strands: Learning Hair Geometry and Appearance from Multi-view Images., , , , , and . ECCV (33), volume 13693 of Lecture Notes in Computer Science, page 73-89. Springer, (2022)