SurfConv: A simple yet effective way to use RGBD data
Paper:
SurfConv: Bridging 3D and 2D Convolution for RGBD Images
Hang Chu, Wei-Chiu Ma, Kaustav Kundu, Raquel Urtasun, Sanja Fidler
CVPR 2018 [pdf]
How it works:
Requirements:
- pytorch-0.2.0
- pypng
Usage:
1. Discretize depth using D4
cd ./D4
python resample_input.py
This will compute depth level boundaries of SurfConv, and generate resampled & masked images/labels for training.
2. Train on KITTI
cd ./train
python surfconv_kitti_scratch_train.py
This will train the model using images generated from step 1.