3D Object Tracking
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Benchmarks
Argoverse CVPR 2020
RTB
Most implemented
Center-based 3D Object Detection and Tracking
Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications
Argoverse: 3D Tracking and Forecasting with Rich Maps
V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception
Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
Papers
Sparse3DTrack: Monocular 3D Object Tracking Using Sparse Supervision
Monocular 3D object tracking aims to estimate temporally consistent 3D object poses across video frames, enabling autonomous agents to reason about scene dynamics. However, existing state-of-the-art approaches are fully …
3D Object TrackingBlinkBud: Detecting Hazards from Behind via Sampled Monocular 3D Detection on a Single Earbud
Failing to be aware of speeding vehicles approaching from behind poses a huge threat to the road safety of pedestrians and cyclists. In this paper, we propose BlinkBud, which utilizes a single earbud and a paired phone t…
Reinforcement Learning3D Object TrackingDepth EstimationUniLION: Towards Unified Autonomous Driving Model with Linear Group RNNs
Although transformers have demonstrated remarkable capabilities across various domains, their quadratic attention mechanisms introduce significant computational overhead when processing long-sequence data. In this paper,…
3D Object DetectionTemporal Sequences3D Object TrackingAutonomous DrivingDIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking
State estimation is challenging for 3D object tracking with high maneuverability, as the target's state transition function changes rapidly, irregularly, and is unknown to the estimator. Existing work based on interactin…
3D Object TrackingObject TrackingState EstimationSelf-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving
The significant achievements of pre-trained models leveraging large volumes of data in the field of NLP and 2D vision inspire us to explore the potential of extensive data pre-training for 3D perception in autonomous dri…
3D Object Detection3D Object TrackingAutonomous DrivingBEV Segmentation+4Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction
DUSt3R has recently shown that one can reduce many tasks in multi-view geometry, including estimating camera intrinsics and extrinsics, reconstructing the scene in 3D, and establishing image correspondences, to the predi…
3D Object Tracking3D ReconstructionDepth EstimationDepth Prediction+5