Rethinking Transformer-based Set Prediction for Object Detection

Last update: Dec 03, 2022

Related tags

Deep Learning TSP-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}
}

Owner

Zhiqing Sun

Third-year Ph.D. student at LTI, CMU

GitHub Repository

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Rethinking Transformer-based Set Prediction for Object Detection

Related tags

Overview

Rethinking Transformer-based Set Prediction for Object Detection

Prerequisites

Rreproducing Results

Citation

Owner

Zhiqing Sun

Implementation of FSGNN

Gauge equivariant mesh cnn

An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

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