Building upon this database, we introduce a baseline framework named <b>Embodied Perceptron</b>. It is capable of processing an arbitrary number of multi-modal inputs and demonstrates remarkable 3D perception capabilities, both within the two series of benchmarks we set up, i.e., fundamental 3D perception tasks and language-grounded tasks, and <b>in the wild</b>.

-\[2025-01\] We are delighted to present the official release of[MMScan-devkit](https://github.com/OpenRobotLab/EmbodiedScan/tree/mmscan), which encompasses a suite of data processing utilities, benchmark evaluation tools, and adaptations of some models for the MMScan benchmarks. We invite you to explore these resources and welcome any feedback or questions you may have!

-\[2024-09\] We are pleased to announce the release of EmbodiedScan v2 beta, with original annotations on newly added~5k scans from ARKitScenes and the beta version of MMScan's annotations on the original 5k scans. Fill in the[form](https://docs.google.com/forms/d/e/1FAIpQLScUXEDTksGiqHZp31j7Zp7zlCNV7p_08uViwP_Nbzfn3g6hhw/viewform) to apply for downloading. Welcome for any feedback!

-\[2024-08\] We preliminarily release the[sample data](https://drive.google.com/file/d/1Y1_LOE35NpsnkneYElvNwuuR6-OAbwPm/view?usp=sharing) of[MMScan](https://tai-wang.github.io/mmscan/) and the full release will be ready with ARKitScenes' annotations this month, which will be announced via emails to the community. Please stay tuned!

-\[2024-06\] The report of our follow-up work with the most-ever hierarchical grounded language annotations,[MMScan](https://tai-wang.github.io/mmscan/), has been released. Welcome to talk with us about EmbodiedScan and MMScan at Seattle, CVPR 2024!