Visual Computing TUM
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- Helen Jennings
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1
2 Visual Computing TUM
3 Visual Computing TUM
4 BundleFusion Real-time 3D Reconstruction Scalable scene representation Global alignment and re-localization TOG 17 [Dai et al.]: BundleFusion
5 Real-time 3D Reconstruction TOG 17 [Dai et al.]: BundleFusion
6 Understanding the 3D Scans chair? chair? chair? chair? chair? TOG 17 [Dai et al.]: BundleFusion
7 3D Object Classification 3D Convolutional Neural Network operating on Voxel Grid CVPR 16 [Qi et al.]: 3D CNNs
8 3D Object Classification Synthetic Data Real Data CVPR 16 [Qi et al.]: 3D CNNs
9 ScanNet: Annotated 3D Reconstructions CVPR 17 (spotlight) [Dai et al.]: ScanNet
10 ScanNet Data Annotation CVPR 17 (spotlight) [Dai et al.]: ScanNet
11 ScanNet CVPR 17 (spotlight) [Dai et al.]: ScanNet
12 ScanNet Statistics CVPR 17 (spotlight) [Dai et al.]: ScanNet
13 CVPR 17 (spotlight) [Dai et al.]: ScanNet ScanNet Tasks: 3D Object Classification Synthetic Prev. Real Ours Lots of real-world data matters!
14 ScanNet Tasks 3D Object Classification 3D Semantic Segmentation 3D Instance Segmentation
15 ScanNet 2D Projections Color Depth Labels 2.5 mio annotated images for 2D object classification, semantic, and instance segmentation CVPR 17 (spotlight) [Dai et al.]: ScanNet
16 ScanNet v1 Problems Annotations are incomplete Test set is public -> people cheat
17 ScanNet v2: 3D Scene Understanding Benchmark New annotations for all 1513 original scans (by experts)!
18 ScanNet v2: 3D Scene Understanding Benchmark New annotations for all 1513 original scans (by experts)! 90% annotation coverage vs previous 63% annotation coverage
19 ScanNet v2: 3D Scene Understanding Benchmark New annotations for all 1513 original scans (by experts)! 90% annotation coverage vs previous 63% annotation coverage Annotated spurious geometry removed from meshes New room type classifications for all 1513 original scans (24 room types) New hidden test set for benchmarking (100 scans) Benchmark Tasks! Multi-view 2d 3D (+optional multi-view) Check it out
20 ScanNet v2: 3D Semantic Segmentation Task
21 ScanNet v2: 3D Instance Segmentation Task
22 ScanNet v2: Multi-view 2D Semantic Segmentation Task
23 ScanNet v2: Multi-view 2D Instance Segmentation Task
24 ScanNet v2: Room Type Classification Task Room type classification ( 13 major room types) 2d and/or 3d input Apartment
25 ScanNet v2: Benchmark Evaluation Evaluation in 2D evaluation over image pixels Evaluation in 3D evaluation over mesh vertices Hidden test sets and automated evaluation scripts!
26 ScanNet v2: Benchmark Evaluation Online since CVPR
27 ScanNet v2: Benchmark Evaluation
28 ScanNet v2: Benchmark Evaluation
29 ScanNet v2: Benchmark Evaluation
30 ScanNet v2: Benchmark Evaluation
31 3D Semantic Segmentation
32 3D Semantic Segmentation CVPR 17 (spotlight) [Dai et al.]: ScanNet
33 CVPR 17 (spotlight) [Dai et al.]: ScanNet ScanNet Tasks: 3D Semantic Segmentation Semantic 3D Segmentation
34 ScanNet Tasks: 3D Semantic Segmentation CVPR 17 (spotlight) [Dai et al.]: ScanNet
35 3DMV: Semantic 3D Segmentation ECCV 18 [Dai and Niessner 18]: 3DMV
36 3DMV: Semantic 3D Segmentation Under submission [Dai and Niessner 18]: 3DMV
37 3DMV: Semantic 3D Segmentation ECCV 18 [Dai and Niessner 18]: 3DMV
38 3DMV: 2D -> 3D Projections ECCV 18 [Dai and Niessner 18]: 3DMV
39 3DMV: 2D Input -> 3D Convs ECCV 18 [Dai and Niessner 18]: 3DMV
40 3DMV: Geo only vs Voxel Colors ECCV 18 [Dai and Niessner 18]: 3DMV
41 3DMV: Geometry vs Color Features ECCV 18 [Dai and Niessner 18]: 3DMV
42 3DMV: Geometry vs Color Features ECCV 18 [Dai and Niessner 18]: 3DMV
43 3DMV: More Views Helps ECCV 18 [Dai and Niessner 18]: 3DMV
44 3DMV: Semantic 3D Segmentation ECCV 18 [Dai and Niessner 18]: 3DMV
45 3D Scene Understanding + Combination of Multi-view + 3D works extremely well + Great way to combine multiple frames (best perf. so far) - Instances are missing (ongoing work ) - Still interesting question: what is right 3D representation
46 Thank You ScanNet Team Angela Dai Angel Chang Thomas Funkhouser Maciej Halber Manolis Savva
47
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