CSPN_monodepth
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Published
20 hours ago •
dontLoveBugs
dontLoveBugs
Unofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network
CSPN implemented in Pytorch 0.4.1
Introduction
This is a PyTorch(0.4.1) implementation of Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network. At present, we can provide train script in NYU Depth V2 dataset for depth completion and monocular depth estimation. KITTI will be available soon!
Faster Implementation
We re-implement CSPN using Pixel-Adaptive Convolution.
Multi_GPU
The implementation of multi-gpus is based on inplace abn.
Results
| Method | Implementation details | rml | rmse | log10 | Delta1 | Delta2 | Delta3 |
|---|---|---|---|---|---|---|---|
| Paper | batch size=24 epoch=40 | 0.016 | 0.117 | - | 0.992 | 0.999 | 1.000 |
| Our_impl | batch size=8 iteration=100k | 0.018 | 0.127 | 0.008 | 0.991 | 0.998 | 1.000 |
| Our_CSPN | batch size=8 iteration=100k | 0.018 | 0.127 | 0.008 | 0.991 | 0.998 | 1.000 |
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Unofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network