chaoer / CSPN_monodepth

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

Third Libs

inplace abn

Pixel-Adaptive Convolution