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hdong51/Human-Animal-Cartoon

Human-Animal-Cartoon dataset Our Human-Animal-Cartoon (HAC) dataset consists of seven actions (‘sleeping’, ‘watching tv’, ‘eating’, ‘drinking’, ‘swimming’, ‘running’, and ‘opening door’) performed by humans, animals, and cartoon figures, forming three different domains. We collect 3381 video clips from the internet with around 1000 for each domain and provide three modalities in our dataset: video, audio, and pre-computed optical flow. The dataset can be used for Multi-modal… See the full description on the dataset page: https://huggingface.co/datasets/hdong51/Human-Animal-Cartoon.

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face

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Dataset Card

Human-Animal-Cartoon dataset

Our Human-Animal-Cartoon (HAC) dataset consists of seven actions (‘sleeping’, ‘watching tv’, ‘eating’, ‘drinking’, ‘swimming’, ‘running’, and ‘opening door’) performed by humans, animals, and cartoon figures, forming three different domains. We collect 3381 video clips from the internet with around 1000 for each domain and provide three modalities in our dataset: video, audio, and pre-computed optical flow.

The dataset can be used for Multi-modal Domain Generalization and Adaptation. More details are in SimMMDG paper and code.

Related Projects

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

MOOSA: Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision

MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities

Citation

If you find our dataset useful in your research please consider citing our paper:

@inproceedings{dong2023SimMMDG,
    title={Sim{MMDG}: A Simple and Effective Framework for Multi-modal Domain Generalization},
    author={Dong, Hao and Nejjar, Ismail and Sun, Han and Chatzi, Eleni and Fink, Olga},
    booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
    year={2023}
}