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3D Reconstruction is an ill-posed Problem
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Classroom Contents
Constraining 3D Fields for Reconstruction and View Synthesis
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- 1 Neural Shape and Appearance Representations
- 2 NeRF Results with 3 Input Views
- 3 Shape-Appearance Ambiguity
- 4 RegNeRF: Overview
- 5 RegNeRF: Scene Space Annealing
- 6 RegNeRF: Ablation Study
- 7 3D Reconstruction is an ill-posed Problem
- 8 Depth Map Prediction from a Single Image
- 9 OmniData: Vision Data from 3D Scans
- 10 MonoSDF: Monocular Geometric Cues for Reconstruction
- 11 MonoSDF: Ablation Study on Replica Dataset
- 12 MonoSDF: Ablation Study on ScanNet
- 13 TensoRF: Tensorial Radiance Fields
- 14 TensoRF: 4D Representation - CANDECOMP/PARAFAC (CP) vs.
- 15 TensoRF: Fast Training
- 16 TensoRF: Tensor Decomposition
- 17 TensoRF: CP Decomposition
- 18 TensoRF: CP vs. VM Decomposition
- 19 TensoRF: VM Decomposition
