POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery

The project is an official implementation of our paper POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery, CVPR 2023.

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Please check image_classification folder for Image Classification Part (Section 4.1 in our paper) and human_mesh_recovery folder for Human Mesh Recovery Part.

Experiments

Visualizations

Citing

If our code helps your research, please consider citing the following paper:

@inproceedings{zheng2023potter,
    title={POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery},
    author={Zheng, Ce and Liu, Xianpeng and Qi, Guo-Jun and Chen, Chen},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year={2023}
}

@inproceedings{zheng2023feater,
    title={FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER},
    author={Zheng, Ce and Mendieta, Matias and Yang, Taojiannan and Qi, Guo-Jun and Chen, Chen},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year={2023}
}