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Papers › Joint 3D Proposal Generation and Object Detection from View Aggregation

Joint 3D Proposal Generation and Object Detection from View Aggregation

6 Dec 2017arXiv:1712.02294archive 2025-07-28

Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, Steven Waslander

We present AVOD, an Aggregate View Object Detection network for autonomous driving scenarios. The proposed neural network architecture uses LIDAR point clouds and RGB images to generate features that are shared by two subnetworks: a region proposal network (RPN) and a second stage detector network. The proposed RPN uses a novel architecture capable of performing multimodal feature fusion on high resolution feature maps to generate reliable 3D object proposals for multiple object classes in road scenes. Using these proposals, the second stage detection network performs accurate oriented 3D bounding box regression and category classification to predict the extents, orientation, and classification of objects in 3D space. Our proposed architecture is shown to produce state of the art results on the KITTI 3D object detection benchmark while running in real time with a low memory footprint, making it a suitable candidate for deployment on autonomous vehicles. Code is at: https://github.com/kujason/avod

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Code

kujason/avod officialmentioned in papermentioned on GitHubtf report
Fredrik00/avod mentioned on GitHubtf report
asharakeh/kitti_native_evaluation mentioned on GitHubpytorch report
kujason/ip_basic mentioned on GitHub report

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Tasks

3D Object DetectionAutonomous DrivingAutonomous VehiclesGeneral ClassificationObjectObject DetectionRegion Proposalobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Object Detection KITTI Cars Easy AVOD + Feature Pyramid AP 81.94% #21 of 26 Archive leaderboard report
3D Object Detection KITTI Cars Hard AVOD + Feature Pyramid AP 66.38% #19 of 25 Archive leaderboard report
3D Object Detection KITTI Cyclists Easy AVOD + Feature Pyramid AP 64.0% #11 of 12 Archive leaderboard report
3D Object Detection KITTI Cyclists Hard AVOD + Feature Pyramid AP 46.61% #11 of 12 Archive leaderboard report
3D Object Detection KITTI Cyclists Moderate AVOD + Feature Pyramid AP 52.18% #12 of 13 Archive leaderboard report
3D Object Detection KITTI Pedestrians Easy AVOD + Feature Pyramid AP 50.8% #7 of 9 Archive leaderboard report
3D Object Detection KITTI Pedestrians Hard AVOD + Feature Pyramid AP 40.88% #5 of 9 Archive leaderboard report
3D Object Detection KITTI Pedestrians Moderate AVOD + Feature Pyramid AP 42.81% #8 of 12 Archive leaderboard report
Birds Eye View Object Detection KITTI Cars Easy AVOD-FPN AP 88.53 #7 of 9 Archive leaderboard report
Birds Eye View Object Detection KITTI Cars Moderate AVOD-FPN AP 83.79% #7 of 9 Archive leaderboard report
Birds Eye View Object Detection KITTI Cyclists Moderate AVOD-FPN AP 57.48% #5 of 6 Archive leaderboard report
Birds Eye View Object Detection KITTI Pedestrians Moderate AVOD-FPN AP 51.05% #3 of 6 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

RPN

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