Update README.md

README.md

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 # **UniOcc**: A Unified Benchmark for Occupancy Forecasting and Prediction in Autonomous Driving
 
-[Paper](https://arxiv.org/)
+![License](https://img.shields.io/badge/license-MIT-blue.svg)
+[![arXiv](https://img.shields.io/badge/arXiv-2503.24381-<COLOR>.svg)](https://arxiv.org/abs/2503.24381)
+[![GitHub](https://img.shields.io/badge/GitHub-UniOcc-Blue.svg)](https://github.com/tasl-lab/UniOcc)
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+
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+<img src="https://github.com/tasl-lab/UniOcc/blob/main/figures/uniocc_overview.png?raw=true" alt="Alt Text" style="width:80%; height:auto;">
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+UniOcc is a unified framework for occupancy forecasting, single-frame occupancy prediction, and occupancy flow estimation in autonomous driving. By integrating multiple real-world (nuScenes, Waymo) and synthetic (CARLA, OpenCOOD) datasets, UniOcc enables multi-domain training, seamless cross-dataset evaluation, and robust benchmarking across diverse driving environments.
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+This dataset contains the data for **UniOcc**. 
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+For data semantics and API please refer to our Github page [UniOcc](https://github.com/tasl-lab/UniOcc) for detailed instructions.
 
-Please refer to our Github page [UniOcc](https://github.com/tasl-lab/UniOcc) for instructions.