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NeuralHOFusion: Neural Volumetric Rendering Under Human-Object Interactions

CVPR 2022 · 3D vision › 3D generation · approach: Monocular 3D object reconstruction · 33 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
combine non-rigid key-volume fusion with neural implicit reconstruction and normal refinement (ablation)NeuralHOFusion human geometry · Human geometryP2S×10⁻⁴: 7.7407 -> 2.855Helped
add normal refinement (ablation)NeuralHOFusion human geometry · Human geometryP2S×10⁻⁴: 3.1425 -> 2.855Helped
add the template-aid object tracking pipeline (ablation)NeuralHOFusion object geometry · Object geometryP2S×10⁻⁴: 35.138 -> 11.480Helped
add normal refinement (ablation)NeuralHOFusion object geometry · Object geometryP2S×10⁻⁴: 11.529 -> 11.480Helped
use layer-wise neural human blending instead of albedo-volume texturing (ablation)NeuralHOFusion human rendering · Human texturePSNR: 26.758 -> 30.040Helped
use layer-wise neural human blending instead of naive neural blending (ablation)NeuralHOFusion human rendering · Human texturePSNR: 25.983 -> 30.040Helped
use temporal neural object blending with non-occluded observations (ablation)NeuralHOFusion object rendering · Object texturePSNR: 33.455 -> 37.901Helped
use temporal neural object blending instead of naive neural blending (ablation)NeuralHOFusion object rendering · Object texturePSNR: 30.760 -> 37.901Helped
increase the input camera count from two to six (ablation)NeuralHOFusion · Human-object interaction scenestexture qualityHelped
combine the full NeuralHOFusion pipeline rather than using comparison methodsHuman-object interaction rendering · Human-object interactionsPSNR: 27.526 -> 33.59Helped
combine the full NeuralHOFusion pipeline rather than using comparison methodsHuman-object interaction geometry · Human-object interactionsP2S×10⁻⁴: 5.770 -> 2.692Helped

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