Add model card
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by nielsr HF Staff - opened
README.md
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license: apache-2.0
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license: apache-2.0
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pipeline_tag: any-to-any
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# EgoM2P: Egocentric Multimodal Multitask Pretraining
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**EgoM2P** (ICCV 2025, EgoVis Distinguished Paper Award) is a large-scale egocentric multimodal and multitask model pretrained on eight egocentric datasets. It handles four modalities — RGB and depth video, gaze dynamics, and camera trajectories — and supports tasks such as monocular egocentric depth estimation, camera tracking, gaze estimation, and conditional egocentric video synthesis.
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- **Paper:** [EgoM2P: Egocentric Multimodal Multitask Pretraining](https://huggingface.co/papers/2506.07886)
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- **Project page:** [https://egom2p.github.io](https://egom2p.github.io)
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- **Code:** [https://github.com/ligengen/EgoM2P](https://github.com/ligengen/EgoM2P)
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The pretrained model weights and tokenizers are available in this repository. Please refer to the GitHub repository for installation, data preparation, tokenization, training, and inference instructions.
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