EfficientMonoHair achieves strand-level hair reconstruction from monocular video with quality comparable to state-of-the-art methods but nearly an order of magnitude faster by using fusion-patch multi-view optimization and parallel hair-growing.
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2 Pith papers cite this work, alongside 132 external citations. Polarity classification is still indexing.
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GaNI combines NeuS geometry reconstruction with a light-position-aware inverse neural radiosity stage that adds implicit near-field modeling, surface angle loss, and roughness smoothness priors to recover reflectance parameters from co-located light-camera captures.
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EfficientMonoHair: Fast Strand-Level Reconstruction from Monocular Video via Multi-View Direction Fusion
EfficientMonoHair achieves strand-level hair reconstruction from monocular video with quality comparable to state-of-the-art methods but nearly an order of magnitude faster by using fusion-patch multi-view optimization and parallel hair-growing.
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GaNI: Global and Near Field Illumination Aware Neural Inverse Rendering
GaNI combines NeuS geometry reconstruction with a light-position-aware inverse neural radiosity stage that adds implicit near-field modeling, surface angle loss, and roughness smoothness priors to recover reflectance parameters from co-located light-camera captures.