## InternImage-based Baseline for CVPR23 Occupancy Prediction Challenge!!!! We improve our baseline with a more powerful image backbone: **InternImage**, which shows its excellent ability within a series of leaderboards and benchmarks, such as *COCO* and *nuScenes*. #### 1. Requirements ```bash python>=3.8 torch==1.12 # recommend mmcv-full>=1.5.0 mmdet==2.24.0 mmsegmentation==0.24.0 timm numpy==1.22 mmdet3d==0.18.1 # recommend ``` ### 2. Install DCNv3 for InternImage ```bash cd projects/mmdet3d_plugin/bevformer/backbones/ops_dcnv3 bash make.sh # requires torch>=1.10 ``` ### 3. Train with InternImage-Small ```bash ./tools/dist_train.sh projects/configs/bevformer/bevformer_intern-s_occ.py 8 # consumes less than 14G memory ``` Notes: InatenImage provides abundant pre-trained model weights that can be used!!! ### 4. Performance compared to baseline | model name | weight | mIoU | others | barrier | bicycle | bus | car | construction_vehicle | motorcycle | pedestrian | traffic_cone | trailer | truck | driveable_surface | other_flat | sidewalk | terrain | manmade | vegetation | | ---------------------- | :---------------------------------------------------------------------------------------------------: | :---: | :----: | :-----: | :-----: | :---: | :---: | :------------------: | :--------: | :--------: | :----------: | :-----: | :---: | :---------------: | :--------: | :------: | :-----: | :-----: | :--------: | | bevformer_intern-s_occ | [Google Drive](https://drive.google.com/file/d/1LV9K8hrskKf51xY1wbqTKzK7WZmVXEV_/view?usp=sharing) | 25.11 | 6.93 | 35.57 | 10.40 | 35.97 | 41.23 | 13.72 | 20.30 | 21.10 | 18.34 | 19.18 | 28.64 | 49.82 | 30.74 | 31.00 | 27.44 | 19.29 | 17.29 | | bevformer_base_occ | [Google Drive](https://drive.google.com/file/d/1NyoiosafAmne1qiABeNOPXR-P-y0i7_I/view?usp=share_link) | 23.67 | 5.03 | 38.79 | 9.98 | 34.41 | 41.09 | 13.24 | 16.50 | 18.15 | 17.83 | 18.66 | 27.70 | 48.95 | 27.73 | 29.08 | 25.38 | 15.41 | 14.46 | ## Challenge Timeline - Pending - Challenge Period Open. - Jun 01, 2023 - Challenge Period End. - Jun 03, 2023 - Finalist Notification. - Jun 10, 2023 - Technical Report Deadline. - Jun 12, 2023 - Winner Announcement.

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## Leaderboard To be released.

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## License Before using the dataset, you should register on the website and agree to the terms of use of the [nuScenes](https://www.nuscenes.org/nuscenes). All code within this repository is under [Apache License 2.0](./LICENSE).

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