Rethinking Transformer-based Set Prediction for Object Detection

Overview

Rethinking Transformer-based Set Prediction for Object Detection

Here are the code for the ICCV paper. The code is adapted from Detectron2 and AdelaiDet.

All the model are trained on 4 V100 GPUs.

Prerequisites

Modify the environment name and environment prefix in environment.yml and run

conda env create -f environment.yml
git clone https://github.com/facebookresearch/detectron2.git
cd detectron2
git reset --hard b88c6c06563e4db1139aafbd6d8d97d1fa7a57e4
pip install -e .

Rreproducing Results

For TSP-FCOS,

bash tsp_fcos.sh

For TSP-RCNN,

bash tsp_rcnn.sh

Citation

@InProceedings{Sun_2021_ICCV,
    author    = {Sun, Zhiqing and Cao, Shengcao and Yang, Yiming and Kitani, Kris M.},
    title     = {Rethinking Transformer-Based Set Prediction for Object Detection},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {3611-3620}
}
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Comments
  • Run the error in the trin_net_rcnn.py

    Run the error in the trin_net_rcnn.py

    Hello, I encountered errors in the picture during the process of running the program. Excuse me, is Troi in the picture a module in Python? But after installing the error in the picture, I hope you can help to point out. image

    opened by 7linlin 2
  • how to train/infer with encoder-only experiment?

    how to train/infer with encoder-only experiment?

    if I understand correctly, without Decoder, you would endup with thousands of proposals from FPN, how to train such MultiHeadAttention?

    Also, correct me if I am wrong. Your work is pretty much a reformulation of RelationNet, which using attention to reduce FP after standard detection pipeline. Therefore convergence is no longer a issue, but still relies on NMS and anchor/point.

    opened by qianyizhang 1
Owner
Zhiqing Sun
Third-year Ph.D. student at LTI, CMU
Zhiqing Sun
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