Skip to content
No description, website, or topics provided.
Python Shell
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
config code May 6, 2019
data code May 6, 2019
docs
kitti_eval code May 6, 2019
.gitignore code May 6, 2019
LICENSE code May 6, 2019
README.md code May 6, 2019
data_loader.py code May 6, 2019
requirements.txt code May 6, 2019
run_all_tests.sh code May 6, 2019
run_depth_test_eval.sh code May 6, 2019
run_depth_train.sh code May 6, 2019
sig_main.py code May 6, 2019
sig_model.py code May 6, 2019
sig_nets.py code May 6, 2019
test_depth.py code May 6, 2019
test_flow.py code May 6, 2019
test_pose.py
utils.py code May 6, 2019

README.md

Semantic Instance Geometry Network for Unsupervised Percepetion

Project page: https://mengyuest.github.io/SIGNet/

This is the implementation of our paper:

Y. Meng, Y. Lu, A. Raj, S. Sunarjo, R. Guo, T. Javidi, G. Bansal, D. Bharadia. "SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception", (CVPR), 2019. [arXiv pdf]

The code is build upon GeoNet

Prerequisite

  1. Ubuntu 16.04, python3, tensorflow-gpu 1.10.1 (test on GTX 1080Ti and RTX 2080Ti with CUDA 9.0)
  2. Better to use virtual environment. For the rest of dependencies, please run pip3 install -r requirements.txt)
  3. Download ground truth depth and our models from https://drive.google.com/open?id=19BFkrfODd3N5IKQJJgqp-pXjbHeYrFf1 (put the models folder directly under the project directory)
  4. Download KITTI evaluation dataset from https://drive.google.com/open?id=1kYNKqIhArAD03WNr4_FZCYRRWo0WT31P (move it two levels upon the project directory, i.e. mv -f data ../../data)

Inference for Depth

  1. Run bash run_all_tests.sh then wait for 2~4 minutes. Results are related to Table 1 ~ Table 4 in our paper.

Training on KITTI

  1. Follow the Data preparation instructions from GeoNet.
  2. Prepare for semantic lables (semantic-level: DeeplabV3+, instance-level: Mask-RCNN)
  3. Quick training: run bash run_depth_train.sh config/foobar.cfg where foobar.cfg is the configuration filename you need to specify.
  4. Logs will be saved in ${CHECKPOINT_DIR}/logs/ defined in foobar.cfg file
You can’t perform that action at this time.