open-mmlab · ZwwWayne · Jul 2, 2021 · Jul 1, 2021 · Jul 1, 2021 · Jul 2, 2021
diff --git a/README.md b/README.md
@@ -8,7 +8,7 @@
 [![license](https://img.shields.io/github/license/open-mmlab/mmdetection3d.svg)](https://github.com/open-mmlab/mmdetection3d/blob/master/LICENSE)
 
 
-**News**: We released the codebase v0.14.0.
+**News**: We released the codebase v0.15.0.
 
 In the recent [nuScenes 3D detection challenge](https://www.nuscenes.org/object-detection?externalData=all&mapData=all&modalities=Any) of the 5th AI Driving Olympics in NeurIPS 2020, we obtained the best PKL award and the second runner-up by multi-modality entry, and the best vision-only results.
 
@@ -62,7 +62,7 @@ This project is released under the [Apache 2.0 license](LICENSE).
 
 ## Changelog
 
-v0.14.0 was released in 1/6/2021.
+v0.15.0 was released in 1/7/2021.
 Please refer to [changelog.md](docs/changelog.md) for details and release history.
 
 ## Benchmark and model zoo

diff --git a/README_zh-CN.md b/README_zh-CN.md
@@ -8,7 +8,7 @@
 [![license](https://img.shields.io/github/license/open-mmlab/mmdetection3d.svg)](https://github.com/open-mmlab/mmdetection3d/blob/master/LICENSE)
 
 
-**新闻**: 我们发布了版本v0.14.0.
+**新闻**: 我们发布了版本v0.15.0.
 
 在第三届[ nuScenes 3D 检测挑战赛](https://www.nuscenes.org/object-detection?externalData=all&mapData=all&modalities=Any)（第五届 AI Driving Olympics, NeurIPS 2020）中，我们获得了最佳 PKL 奖、第三名和最好的纯视觉的结果，相关的代码和模型将会在不久后发布。
 
@@ -62,7 +62,7 @@ MMDetection3D 是一个基于 PyTorch 的目标检测开源工具箱, 下一代
 
 ## 更新日志
 
-最新的版本 v0.14.0 在 2021.06.01发布。
+最新的版本 v0.15.0 在 2021.07.01发布。
 如果想了解更多版本更新细节和历史信息，请阅读[更新日志](docs/changelog.md)。
 
 ## 基准测试和模型库

diff --git a/docs/changelog.md b/docs/changelog.md
@@ -1,5 +1,45 @@
 ## Changelog
 
+### v0.15.0 (1/7/2021)
+
+#### Highlights
+
+- Support [PAConv](https://arxiv.org/abs/2103.14635)
+- Support monocular/multi-view 3D detector [ImVoxelNet](https://arxiv.org/abs/2106.01178) on KITTI
+- Support Transformer-based 3D detection method [Group-Free-3D](https://arxiv.org/abs/2104.00678) on ScanNet
+- Add documentation for tasks including LiDAR-based 3D detection, vision-only 3D detection and point-based 3D semantic segmentation
+- Add dataset documents like ScanNet
+
+#### New Features
+
+- Support Group-Free-3D on ScanNet (#539)
+- Support PAConv modules (#598, #599)
+- Support ImVoxelNet on KITTI (#627, #654)
+
+#### Improvements
+
+- Add unit tests for pipeline functions `LoadImageFromFileMono3D`, `ObjectNameFilter` and `ObjectRangeFilter` (#615)
+- Enhance [IndoorPatchPointSample](https://github.com/open-mmlab/mmdetection3d/blob/master/mmdet3d/datasets/pipelines/transforms_3d.py) (#617)
+- Refactor model initialization methods based MMCV (#622)
+- Add Chinese docs (#629)
+- Add documentation for LiDAR-based 3D detection (#642)
+- Unify intrinsic and extrinsic matrices for all datasets (#653)
+- Add documentation for point-based 3D semantic segmentation (#663)
+- Add documentation of ScanNet for 3D detection (#664)
+- Refine docs for tutorials (#666)
+- Add documentation for vision-only 3D detection (#669)
+- Refine docs for Quick Run and Useful Tools (#686)
+
+
+#### Bug Fixes
+
+- Fix the bug of [BackgroundPointsFilter](https://github.com/open-mmlab/mmdetection3d/blob/master/mmdet3d/datasets/pipelines/transforms_3d.py) using the bottom center of ground truth (#609)
+- Fix [LoadMultiViewImageFromFiles](https://github.com/open-mmlab/mmdetection3d/blob/master/mmdet3d/datasets/pipelines/loading.py) to unravel stacked multi-view images to list to be consistent with DefaultFormatBundle (#611)
+- Fix the potential bug in [analyze_logs](https://github.com/open-mmlab/mmdetection3d/blob/master/tools/analysis_tools/analyze_logs.py) when the training resumes from a checkpoint or is stopped before evaluation (#634)
+- Fix test commands in docs and make some refinements (#635)
+- Fix wrong config paths in unit tests (#641)
+
+
 ### v0.14.0 (1/6/2021)
 
 #### Highlights
@@ -20,7 +60,7 @@
 - Support visualization of detection results and dataset browse for nuScenes Mono-3D dataset (#542, #582)
 - Support faster implementation of KNN (#586)
 - Support RegNetX models on Lyft dataset (#589)
-- Remove a useless parameter [label_weight] from segmentation datasets including [Custom3DSegDataset], [ScanNetSegDataset] and [S3DISSegDataset] (#607)
+- Remove a useless parameter `label_weight` from segmentation datasets including `Custom3DSegDataset`, `ScanNetSegDataset` and `S3DISSegDataset` (#607)
 
 #### Bug Fixes
 - Fix a corrupted lidar data file in Lyft dataset in [data_preparation](https://github.com/open-mmlab/mmdetection3d/tree/master/docs/data_preparation.md) (#546)

diff --git a/docs/getting_started.md b/docs/getting_started.md
@@ -12,8 +12,9 @@ The required versions of MMCV, MMDetection and MMSegmentation for different vers
 
 | MMDetection3D version | MMDetection version | MMSegmentation version | MMCV version |
 |:-------------------:|:-------------------:|:-------------------:|:-------------------:|
-| master | mmdet>=2.12.0 | mmseg>=0.14.1 | mmcv-full>=1.3.2, <=1.4|
-| 0.14.0 | mmdet>=2.10.0, <=2.11.0| mmseg>=0.13.0 | mmcv-full>=1.3.1, <=1.4|
+| master | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4|
+| 0.15.0 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4|
+| 0.14.0 | mmdet>=2.10.0, <=2.11.0| mmseg==0.14.0 | mmcv-full>=1.3.1, <=1.4|
 | 0.13.0 | mmdet>=2.10.0, <=2.11.0| Not required | mmcv-full>=1.2.4, <=1.4|
 | 0.12.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.4|
 | 0.11.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.4|
@@ -94,36 +95,32 @@ pip install mmcv-full
 
 **d. Install [MMDetection](https://github.com/open-mmlab/mmdetection).**
 
-Note:
-
-MMDetection3D v0.14.0 is only compatible with MMDetection version `mmdet>=2.10.0, <=2.11.0`. The future versions will only support `mmdet>=2.12.0` since v0.15.0 (to be released in July).
-
 ```shell
-pip install mmdet==2.11.0
+pip install mmdet==2.14.0
 ```
 
 Optionally, you could also build MMDetection from source in case you want to modify the code:
 
 ```shell
 git clone https://github.com/open-mmlab/mmdetection.git
 cd mmdetection
-git checkout v2.11.0 # switch to v2.11.0 branch
+git checkout v2.14.0 # switch to v2.14.0 branch
 pip install -r requirements/build.txt
 pip install -v -e . # or "python setup.py develop"
 ```
 
 **e. Install [MMSegmentation](https://github.com/open-mmlab/mmsegmentation).**
 
 ```shell
-pip install mmsegmentation==0.14.0
+pip install mmsegmentation==0.14.1
 ```
 
 Optionally, you could also build MMSegmentation from source in case you want to modify the code:
 
 ```shell
 git clone https://github.com/open-mmlab/mmsegmentation.git
 cd mmsegmentation
-git checkout v0.14.0 # switch to v0.14.0 branch
+git checkout v0.14.1 # switch to v0.14.1 branch
 pip install -e . # or "python setup.py develop"
 ```
 

diff --git a/mmdet3d/version.py b/mmdet3d/version.py
@@ -1,6 +1,6 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '0.14.0'
+__version__ = '0.15.0'
 short_version = __version__
 
 

diff --git a/requirements/mminstall.txt b/requirements/mminstall.txt
@@ -1,3 +1,3 @@
-mmcv-full>=1.3.1,<=1.4.0
-mmdet>=2.10.0,<=2.11.0
-mmsegmentation>=0.14.0,<=0.14.0
+mmcv-full>=1.3.8,<=1.4.0
+mmdet>=2.14.0,<=3.0.0
+mmsegmentation>=0.14.1,<=1.0.0