Meghna Asthana - Academia.edu (original) (raw)

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Papers by Meghna Asthana

Zenodo (CERN European Organization for Nuclear Research), Jun 13, 2023

arXiv (Cornell University), Jul 14, 2022

Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF ... more Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF [25] with a physically-based image formation model. The geometry network predicts density and surface normal direction at each position in the volume. A neural BRDF and shadow network predict reflected scene radiance for the point which is then volume rendered using predicted density as for NeRF. The resulting model is relightable while also improving geometric information using multi-light observations.

European Conference on Visual Media Production

Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF ... more Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF [25] with a physically-based image formation model. The geometry network predicts density and surface normal direction at each position in the volume. A neural BRDF and shadow network predict reflected scene radiance for the point which is then volume rendered using predicted density as for NeRF. The resulting model is relightable while also improving geometric information using multi-light observations.

Zenodo (CERN European Organization for Nuclear Research), Jun 13, 2023

arXiv (Cornell University), Jul 14, 2022

Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF ... more Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF [25] with a physically-based image formation model. The geometry network predicts density and surface normal direction at each position in the volume. A neural BRDF and shadow network predict reflected scene radiance for the point which is then volume rendered using predicted density as for NeRF. The resulting model is relightable while also improving geometric information using multi-light observations.

European Conference on Visual Media Production

Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF ... more Volume Renderer Figure 1: We replace the view-conditioned black box radiance predicted by a NeRF [25] with a physically-based image formation model. The geometry network predicts density and surface normal direction at each position in the volume. A neural BRDF and shadow network predict reflected scene radiance for the point which is then volume rendered using predicted density as for NeRF. The resulting model is relightable while also improving geometric information using multi-light observations.

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