📘Documentation | 🛠️Installation |

STF module is the Fusion Module for Improving Video Object Detection and it is a part of the OpenMMLab project.

The main branch works with PyTorch 1.8+.

Please refer to Installation for installation instructions.

Please see Overview for the general introduction of MMDetection. You need to follow the steps defined in the docs.

To train the model, use the following command:

python tools/train configs/centernet/hrnet.py

For detailed user guides and advanced guides, please refer to our documentation:

• User Guides

  • Train & Test
    • Learn about Configs
    • Inference with existing models
    • Dataset Prepare
    • Test existing models on standard datasets
    • Train predefined models on standard datasets
    • Train with customized datasets
    • Train with customized models and standard datasets
    • Finetuning Models
    • Test Results Submission
    • Weight initialization
    • Use a single-stage detector as RPN
    • Semi-supervised Object Detection
  • Useful Tools

In this repo, we used the following datasets:

1. KITTI MOTS Dataset
2. Cityscapes Dataset
3. UAVDT Dataset

These are the results on Cityscape, KITTI (MOT) and UAVDT, respectively.

Please refer to FAQ for frequently asked questions.

We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC),[funding reference number RGPIN-2020-04633].

If you use this module in your research, please cite this project. (https://arxiv.org/abs/2402.10752)

This project is released under the Apache 2.0 license.