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HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimation

Wencan Cheng, Eun-ji Kim and Jong Hwan Ko

European Conference on Computer Vision (ECCV), 2024

Prerequisities

Our model is trained and tested under:

  1. Prepare dataset

    please download the NYU Hand dataset

  2. Install PointNet++ CUDA operations

    follow the instructions in the './pointnet2' for installation

  3. Evaluate

    set the "--dataset_path" paramter in the test_nyu.sh as the path saved the generated testing set

    execute sh test_nyu.sh

    we provided the pre-trained models ('./pretrained_model/nyu_handdagt_3stacks/best_model.pth') for NYU

  4. If a new training process is needed, please execute the following instructions after step 1 and 2 are completed

    set the "--dataset_path" paramter in the train_nyu.sh as the path saved the generated traning and testing set respectively

    execute sh train_nyu.sh

Acknowledgement

We thank repo for the image-point cloud framework.