README.md

H3DNet: 3D Object Detection Using Hybrid Geometric Primitives

Introduction

We implement H3DNet and provide the result and checkpoints on ScanNet datasets.

@inproceedings{zhang2020h3dnet,
    author = {Zhang, Zaiwei and Sun, Bo and Yang, Haitao and Huang, Qixing},
    title = {H3DNet: 3D Object Detection Using Hybrid Geometric Primitives},
    booktitle = {Proceedings of the European Conference on Computer Vision},
    year = {2020}
}

Results

ScanNet

Backbone	Lr schd	Mem (GB)	Inf time (fps)	AP@0.25	AP@0.5	Download
MultiBackbone	3x	7.9		66.43	48.01	model | log

Notice: If your current mmdetection3d version >= 0.6.0, and you are using the checkpoints downloaded from the above links or using checkpoints trained with mmdetection3d version < 0.6.0, the checkpoints have to be first converted via tools/model_converters/convert_h3dnet_checkpoints.py:

python ./tools/model_converters/convert_h3dnet_checkpoints.py ${ORIGINAL_CHECKPOINT_PATH} --out=${NEW_CHECKPOINT_PATH}

Then you can use the converted checkpoints following getting_started.md.