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Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes From a Single Image

CVPR 2020 · 3D vision › 3D generation · approach: Generative indoor scene synthesis · 240 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
jointly train layout, object detection, and mesh reconstruction with cooperative and global losses (ablation)Total3DUnderstanding · SUN RGB-D3D object detection mAP: 20.19 -> 26.38Helped
jointly train layout, object detection, and mesh reconstruction with cooperative and global losses (ablation)Total3DUnderstanding · SUN RGB-Dlayout IoU: 57.63 -> 58.87Helped
add relational features to ODN (ablation)Total3DUnderstanding · SUN RGB-D3D object detection mAP: 20.19 -> 23.32Helped
add cooperative loss (ablation)Total3DUnderstanding · SUN RGB-Dlayout IoU: 57.63 -> 58.21Helped
add global scene geometry loss (ablation)Total3DUnderstanding · SUN RGB-D3D object detection mAP: 20.19 -> 24.59Helped
use cooperative and global losses together (ablation)Total3DUnderstanding · SUN RGB-D3D object detection mAP: 24.59 -> 25.62Helped
cut mesh edges rather than remove faces (ablation)Total3DUnderstanding mesh generation · Pix3Dmean mesh Chamfer distance (10^-3): 8.84 -> 8.36Helped
use local density rather than a distance threshold for topology modification (ablation)Total3DUnderstanding mesh generation · Pix3Dmean mesh Chamfer distance (10^-3): 8.75 -> 8.36Helped
fine-tune mesh generation on SUN RGB-D partial point clouds (ablation)Total3DUnderstanding mesh generation · Pix3Dsingle-object mesh reconstructionNo clear effect

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