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license: mit |
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# Epona: Autoregressive Diffusion World Model for Autonomous Driving |
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This repository contains the model checkpoints and test meta data in the paper [Epona: Autoregressive Diffusion World Model for Autonomous Driving |
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](https://arxiv.org/abs/2506.24113.pdf). |
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🌏 Project page : [https://kevin-thu.github.io/Epona/](https://kevin-thu.github.io/Epona/). |
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⭐ Code: [https://github.com/Kevin-thu/Epona](https://github.com/Kevin-thu/Epona). |
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It contains four model checkpoints: |
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- `epona_nuplan.pkl`: The base world model trained on NuPlan from scratch; |
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- `epona_nuplan+nusc.pkl`: The world model finetuned on NuScenes based on the base model; |
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- `epona_nuplan+china.pkl`: The world model fintuned on in-house China driving data based on the base model; |
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- `dcae_td_20000.pkl`: The temporal-aware DCAE (downsampling rate=32, channel dim=32, temporal patch size=6) fintuned on NuPlan video clips. |
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And two folders of preprocessed json files: |
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- `test_meta_data_nuplan`: Preprocessed meta infos on NuPlan test set (not including train set); |
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- `meta_data_nusc`: Preprocessed meta infos on NuScenes train set and validation set. |
