Papers 3D Object Tracking
“3D Object Tracking” 태그가 달린 논문 70편 · 필터 해제
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar
Robust perception is a vital component for ensuring safe autonomous and assisted driving. Automotive radar (77 to 81 GHz), which offers weather-resilient sensing, provides a complementary capability to the vision- or LiD…
3D Object Detection3D Object TrackingAutonomous DrivingObject+4Robust 6DoF Pose Estimation Against Depth Noise and a Comprehensive Evaluation on a Mobile Dataset
Robust 6DoF pose estimation with mobile devices is the foundation for applications in robotics, augmented reality, and digital twin localization. In this paper, we extensively investigate the robustness of existing RGBD-…
3D Object Detection3D Object Tracking6D Pose Estimation6D Pose Estimation using RGBD+3The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle tracking
This work presents a novel video dataset recorded from overlapping highway traffic cameras along an urban interstate, enabling multi-camera 3D object tracking in a traffic monitoring context. Data is released from 3 scen…
3D Object TrackingObjectObject TrackingSynchronize Feature Extracting and Matching: A Single Branch Framework for 3D Object Tracking
Siamese network has been a de facto benchmark framework for 3D LiDAR object tracking with a shared-parametric encoder extracting features from template and search region, respectively. This paradigm relies heavily on an …
3D Object TrackingObject TrackingDelving into Motion-Aware Matching for Monocular 3D Object Tracking
Recent advances of monocular 3D object detection facilitate the 3D multi-object tracking task based on low-cost camera sensors. In this paper, we find that the motion cue of objects along different time frames is critica…
3D Multi-Object Tracking3D Object Detection3D Object TrackingMonocular 3D Object Detection+5BOTT: Box Only Transformer Tracker for 3D Object Tracking
Tracking 3D objects is an important task in autonomous driving. Classical Kalman Filtering based methods are still the most popular solutions. However, these methods require handcrafted designs in motion modeling and can…
3D Object TrackingAutonomous DrivingObjectObject TrackingS.T.A.R.-Track: Latent Motion Models for End-to-End 3D Object Tracking with Adaptive Spatio-Temporal Appearance Representations
Following the tracking-by-attention paradigm, this paper introduces an object-centric, transformer-based framework for tracking in 3D. Traditional model-based tracking approaches incorporate the geometric effect of objec…
3D Object TrackingObjectObject TrackingTrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypotheses
3D multi-object tracking (MOT) is vital for many applications including autonomous driving vehicles and service robots. With the commonly used tracking-by-detection paradigm, 3D MOT has made important progress in recent …
3D Multi-Object Tracking3D Object TrackingAutonomous DrivingMulti-Object Tracking+2CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception
Autonomous driving requires an accurate and fast 3D perception system that includes 3D object detection, tracking, and segmentation. Although recent low-cost camera-based approaches have shown promising results, they are…
3D Multi-Object Tracking3D Object Detection3D Object TrackingAutonomous Driving+2BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
We present a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the object. Our method works for arbitrary rigi…
3D Object Detection3D Object Tracking3D Reconstruction6D Pose Estimation+4V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent res…
3D Object Detection3D Object TrackingAutonomous DrivingAutonomous Vehicles+4Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual a…
3D Object Tracking6D Pose Estimation6D Pose Estimation using RGBDObject+1Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications
Digital twin is a problem of augmenting real objects with their digital counterparts. It can underpin a wide range of applications in augmented reality (AR), autonomy, and UI/UX. A critical component in a good digital-tw…
3D Object TrackingObjectObject TrackingRobotic Grasping+1Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
Autonomous driving needs to rely on high-quality 3D object detection to ensure safe navigation in the world. Uncertainty estimation is an effective tool to provide statistically accurate predictions, while the associated…
3D Object Detection3D Object TrackingAutonomous DrivingObject+2Variational Voxel Pseudo Image Tracking
Uncertainty estimation is an important task for critical problems, such as robotics and autonomous driving, because it allows creating statistically better perception models and signaling the model's certainty in its pre…
3D Object Tracking3D Single Object TrackingAutonomous DrivingObject TrackingCC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion
To track the 3D locations and trajectories of the other traffic participants at any given time, modern autonomous vehicles are equipped with multiple cameras that cover the vehicle's full surroundings. Yet, camera-based …
3D Object TrackingAutonomous VehiclesMulti-Object TrackingObject+1CXTrack: Improving 3D Point Cloud Tracking with Contextual Information
3D single object tracking plays an essential role in many applications, such as autonomous driving. It remains a challenging problem due to the large appearance variation and the sparsity of points caused by occlusion an…
3D Object Tracking3D Single Object TrackingAutonomous DrivingObject+1TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM
3D object tracking is a critical task in autonomous driving systems. It plays an essential role for the system's awareness about the surrounding environment. At the same time there is an increasing interest in algorithms…
3D Object TrackingAutonomous DrivingObjectObject Tracking+1MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation
Visual SLAM systems targeting static scenes have been developed with satisfactory accuracy and robustness. Dynamic 3D object tracking has then become a significant capability in visual SLAM with the requirement of unders…
3D Object TrackingAutonomous DrivingDepth EstimationMonocular Depth Estimation+3Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer
With the prevalence of LiDAR sensors in autonomous driving, 3D object tracking has received increasing attention. In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in…
3D Object TrackingAutonomous DrivingObjectObject Tracking+1