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Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition

EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition pdf

image

EventDance++: Language-guided Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition pdf

Update

[09/2024], codes for EventDance++ are in progress. [07/2024], codes for evaluation are released.

Environments

git clone --
cd --
conda create -n evd python=3.9
conda activate evd
pip install -r requirements.txt

Data Preparation

Used Datasets: Event Modality: NMNIST / NCALTECH101 / NCIFAR10 Image Modality: MNIST / CALTECH101 / CIFAR10

datasets/
├── NMIST
│   ├── Test
│   └── Train
├── MNIST
│   ├── image
│   └── raw
├── NCALTECH101
│   ├── accordion
│   │   ...
│   └── yin_yang
├── CALTECH101
│   ├── 101_ObjectCategories
│   └── Annotations

References

We appreciate the previous open-source works: Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy

Citations

If you are interested in this work, please cite the following works:

@inproceedings{zheng2024eventdance,
  title={EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition},
  author={Zheng, Xu and Wang, Lin},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={17448--17458},
  year={2024}
}

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