Highlights

• Support a new multi-modality method ImVoteNet.
• Support pytorch 1.7 and 1.8
• Refactor the structure of tools and train.py/test.py

Bug Fixes

• Fix missing keys coord_type in database sampler config (#345)
• Rename H3DNet configs (#349)
• Fix CI by using ubuntu 18.04 in github workflow (#350)
• Add assertions to avoid 4-dim points being input to points_in_boxes (#357)
• Fix the SECOND results on Waymo in the corresponding README (#363)
• Fix the incorrectly adopted pipeline when adding val to workflow (#370)
• Fix a potential bug when indices used in the backwarding in ThreeNN (#377)
• Fix a compilation error triggered by scatter_points_cuda.cu in pytorch 1.7 (#393)

New Features

• Support LiDAR-based semantic segmentation metrics (#332)
• Support ImVoteNet (#352, #384)
• Support the KNN GPU operation (#360, #371)

Improvements

• Add FAQ for common problems in the documentation (#333)
• Refactor the structure of tools (#339)
• Refactor train.py and test.py (#343)
• Support demo on nuScenes (#353)
• Add 3DSSD checkpoints (#359)
• Update the Bibtex of CenterPoint (#368)
• Add citation format and reference to other OpenMMLab projects in the README (#374)
• Upgrade the mmcv version requirements (#376)
• Add numba and numpy version requirements in FAQ (#379)
• Avoid unnecessary for-loop execution of VFE layer creation (#389)
• Update SUNRGBD dataset documentation to stress the requirements for training ImVoteNet (#391)
• Modify vote head to support 3DSSD (#396)

New Contributors

• @tianweiy made their first contribution in https://github.com/open-mmlab/mmdetection3d/pull/368
• @happynear made their first contribution in https://github.com/open-mmlab/mmdetection3d/pull/363
• @zehuichen123 made their first contribution in https://github.com/open-mmlab/mmdetection3d/pull/389

Full Changelog: https://github.com/open-mmlab/mmdetection3d/compare/v0.11.0...v0.12.0