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Loss functions
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Classroom Contents
Appearance Acquisition for Digital 3D Content Creation
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- 1 Intro
- 2 Geometry + Material
- 3 Image-based appearance acquisition
- 4 RGBD reconstructions
- 5 Projective texture mapping
- 6 Previous works
- 7 Our approach
- 8 Observations
- 9 Similarity: coherence
- 10 Similarity: completeness + coherence
- 11 Consistency
- 12 Patch-base energy function
- 13 Multi-scale optimization
- 14 Comparison against single-view selection
- 15 Acquisition setup
- 16 Learning-based multi-view stereo
- 17 SVBRDF prediction
- 18 Geometry reconstruction
- 19 Volumetric representations
- 20 Relightable reconstructions
- 21 Joint view synthesis and relighting
- 22 Mobile phone captures with flashlight
- 23 Discretized volume rendering
- 24 Learning deep reflectance volumes
- 25 Loss functions
- 26 Comparison to mesh-based methods
- 27 Comparison on synthetic data
- 28 Environment map rendering
- 29 Physically-accurate volume rendering
- 30 More results
- 31 Integration with a physically-based rendere
- 32 Sparse geometry and BRDF acquisition
- 33 Neural representations for scenes
- 34 Generalizable neural representations
- 35 Integration with traditional rendering
