From 41e7c596ebb83b05a4154bb0ac7a28e0b9afd017 Mon Sep 17 00:00:00 2001 From: Waleed Date: Thu, 12 Jul 2018 23:28:18 -0700 Subject: [PATCH] Add Bibtex to README --- README.md | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 6c89e16..5da2f23 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@ The repository includes: * Example of training on your own dataset -The code is documented and designed to be easy to extend. If you use it in your research, please consider referencing this repository. If you work on 3D vision, you might find our recently released [Matterport3D](https://matterport.com/blog/2017/09/20/announcing-matterport3d-research-dataset/) dataset useful as well. +The code is documented and designed to be easy to extend. If you use it in your research, please consider citing this repository (bibtex below). If you work on 3D vision, you might find our recently released [Matterport3D](https://matterport.com/blog/2017/09/20/announcing-matterport3d-research-dataset/) dataset useful as well. This dataset was created from 3D-reconstructed spaces captured by our customers who agreed to make them publicly available for academic use. You can see more examples [here](https://matterport.com/gallery/). # Getting Started @@ -141,6 +141,19 @@ gradients (sum vs mean across batches and GPUs). Or, maybe the official model us clipping to avoid this issue. We do use gradient clipping, but don't set it too aggressively. We found that smaller learning rates converge faster anyway so we go with that. +## Citation +Use this bibtex to cite this repository: +``` +@misc{matterport_maskrcnn_2017, + title={Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow}, + author={Abdulla, Waleed}, + year={2017}, + publisher={Github}, + journal={GitHub repository}, + howpublished={\url{https://github.com/matterport/Mask_RCNN}}, +} +``` + ## Contributing Contributions to this repository are welcome. Examples of things you can contribute: * Speed Improvements. Like re-writing some Python code in TensorFlow or Cython. -- GitLab