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Models/ECC (12 votes)

ECC (12 votes)

Reported on 12 benchmarks across 6 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

Shape Representation Of 3D Point CloudsonModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Object ClassificationonModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Point Cloud ClassificationonModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Point Cloud ReconstructiononModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
Shape Representation Of 3D Point CloudsonModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Object ClassificationonModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Point Cloud ClassificationonModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D Point Cloud ReconstructiononModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901

Methodology2 results

3DonModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3DonModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901

Medical2 results

3D ClassificationonModelNet40
Classification Accuracy· 2017-04-10
83.2
best: 93.6 (Ours)
SOTA
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901
3D ClassificationonModelNet10
Accuracy· 2017-04-10
90
best: 94.93 (PolyNet)
Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs arXiv:1704.02901