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3D Multi-Object Tracking

7 papers with code · Computer Vision

Image: Weng et al

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Greatest papers with code

3D Multi-Object Tracking: A Baseline and New Evaluation Metrics

9 Jul 2019xinshuoweng/AB3DMOT

Additionally, 3D MOT datasets such as KITTI evaluate MOT methods in the 2D space and standardized 3D MOT evaluation tools are missing for a fair comparison of 3D MOT methods.

3D MULTI-OBJECT TRACKING AUTONOMOUS DRIVING

Argoverse: 3D Tracking and Forecasting With Rich Maps

CVPR 2019 argoai/argoverse-api

We use 3D object tracking to mine for more than 300k interesting vehicle trajectories to create a trajectory forecasting benchmark.

3D MULTI-OBJECT TRACKING AUTONOMOUS VEHICLES MOTION FORECASTING OBJECT TRACKING TRAJECTORY FORECASTING

Center-based 3D Object Detection and Tracking

19 Jun 2020tianweiy/CenterPoint

Three-dimensional objects are commonly represented as 3D boxes in a point-cloud.

3D MULTI-OBJECT TRACKING 3D OBJECT DETECTION OBJECT TRACKING

GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning

12 Jun 2020xinshuoweng/GNN3DMOT

As a result, the feature of one object is informed of the features of other objects so that the object feature can lean towards the object with similar feature (i. e., object probably with a same ID) and deviate from objects with dissimilar features (i. e., object probably with different IDs), leading to a more discriminative feature for each object; (2) instead of obtaining the feature from either 2D or 3D space in prior work, we propose a novel joint feature extractor to learn appearance and motion features from 2D and 3D space simultaneously.

3D MULTI-OBJECT TRACKING

GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking With 2D-3D Multi-Feature Learning

CVPR 2020 xinshuoweng/GNN3DMOT

As a result, the feature of one object is informed of the features of other objects so that the object feature can lean towards the object with similar feature (i. e., object probably with a same ID) and deviate from objects with dissimilar features (i. e., object probably with different IDs), leading to a more discriminative feature for each object; (2) instead of obtaining the feature from either 2D or 3D space in prior work, we propose a novel joint feature extractor to learn appearance and motion features from 2D and 3D space simultaneously.

3D MULTI-OBJECT TRACKING

Joint 3D Tracking and Forecasting with Graph Neural Network and Diversity Sampling

17 Mar 2020xinshuoweng/GNNTrkForecast

To evaluate this hypothesis, we propose a unified solution for 3D MOT and trajectory forecasting which also incorporates two additional novel computational units.

3D MULTI-OBJECT TRACKING TRAJECTORY FORECASTING