MMDetection3D V0.13.0 Release
Highlights
- Support a monocular 3D detection method FCOS3D
- Support ScanNet and S3DIS semantic segmentation dataset
- Enhancement of visualization tools for dataset browsing and demos, including support of visualization for multi-modality data and point cloud segmentation.
New Features
- Support ScanNet semantic segmentation dataset (#390)
- Support monocular 3D detection on nuScenes (#392)
- Support multi-modality visualization (#405)
- Support nuImages visualization (#408)
- Support monocular 3D detection on KITTI (#415)
- Support online visualization of semantic segmentation results (#416)
- Support ScanNet test results submission to online benchmark (#418)
- Support S3DIS data pre-processing and dataset class (#433)
- Support FCOS3D (#436, #442, #482, #484)
- Support dataset browse for multiple types of datasets (#467)
- Adding paper-with-code (PWC) metafile for each model in the model zoo (#485)
Improvements
- Support dataset browsing for SUNRGBD, ScanNet or KITTI points and detection results (#367)
- Add the pipeline to load data using file client (#430)
- Support to customize the type of runner (#437)
- Make pipeline functions process points and masks simultaneously when sampling points (#444)
- Add waymo unit tests (#455)
- Split the visualization of projecting points onto image from that for only points (#480)
- Efficient implementation of PointSegClassMapping (#489)
- Use the new model registry from mmcv (#495)
Bug Fixes
- Fix Pytorch 1.8 Compilation issue in the scatter_points_cuda.cu (#404)
- Fix dynamic_scatter errors triggered by empty point input (#417)
- Fix the bug of missing points caused by using break incorrectly in the voxelization (#423)
- Fix the missing
coord_type
in the waymo dataset config (#441) - Fix errors in four unittest functions of configs, test_detectors.py, test_heads.py (#453)
- Fix 3DSSD training errors and simplify configs (#462)
- Clamp 3D votes projections to image boundaries in ImVoteNet (#463)
- Update out-of-date names of pipelines in the config of pointpillars benchmark (#474)
- Fix the lack of a placeholder when unpacking RPN targets in the h3d_bbox_head.py (#508)
- Fix the incorrect value of
K
when creating pickle files for SUN RGB-D (#511)
New Contributors
- @gillbam made their first contribution in #423
- @Divadi made their first contribution in #463
- @virusapex made their first contribution in #511
Full Changelog: v0.12.0...v0.13.0