PackNet-SfM

Reported on 4 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision2 results

Depth EstimationonKITTI Object Tracking Evaluation 2012
Abs Rel· 2019-05-06
0.071
SOTA
3D Packing for Self-Supervised Monocular Depth Estimation arXiv:1905.02693
Depth EstimationonKITTI Eigen split
absolute relative error· 2019-05-06
0.12
best: 0.029 (SPIDepth)
3D Packing for Self-Supervised Monocular Depth Estimation arXiv:1905.02693

Methodology2 results

3DonKITTI Object Tracking Evaluation 2012
Abs Rel· 2019-05-06
0.071
SOTA
3D Packing for Self-Supervised Monocular Depth Estimation arXiv:1905.02693
3DonKITTI Eigen split
absolute relative error· 2019-05-06
0.12
best: 0.029 (SPIDepth)
3D Packing for Self-Supervised Monocular Depth Estimation arXiv:1905.02693