Papers 3D Single Object Tracking
“3D Single Object Tracking” 태그가 달린 논문 43편 · 필터 해제
OSP2B: One-Stage Point-to-Box Network for 3D Siamese Tracking
Two-stage point-to-box network acts as a critical role in the recent popular 3D Siamese tracking paradigm, which first generates proposals and then predicts corresponding proposal-wise scores. However, such a network suf…
3D Single Object TrackingObject TrackingGLT-T++: Global-Local Transformer for 3D Siamese Tracking with Ranking Loss
Siamese trackers based on 3D region proposal network (RPN) have shown remarkable success with deep Hough voting. However, using a single seed point feature as the cue for voting fails to produce high-quality 3D proposals…
3D Single Object TrackingObject TrackingRegion ProposalAn Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
3D single object tracking in LiDAR point clouds (LiDAR SOT) plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching. However, LiDAR point clouds are usu…
3D Single Object TrackingAutonomous DrivingDomain AdaptationObject Tracking+2MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency
3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Insp…
3D Single Object TrackingData AugmentationObject TrackingModeling Continuous Motion for 3D Point Cloud Object Tracking
The task of 3D single object tracking (SOT) with LiDAR point clouds is crucial for various applications, such as autonomous driving and robotics. However, existing approaches have primarily relied on appearance matching …
3D Single Object TrackingAutonomous DrivingObjectObject TrackingMBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors
3D single object tracking has been a crucial problem for decades with numerous applications such as autonomous driving. Despite its wide-ranging use, this task remains challenging due to the significant appearance variat…
3D Single Object TrackingAutonomous DrivingGPUObject TrackingVariational 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 TrackingObject Preserving Siamese Network for Single Object Tracking on Point Clouds
Obviously, the object is the key factor of the 3D single object tracking (SOT) task. However, previous Siamese-based trackers overlook the negative effects brought by randomly dropped object points during backbone sampli…
3D Single Object TrackingObjectObject LocalizationObject TrackingGLT-T: Global-Local Transformer Voting for 3D Single Object Tracking in Point Clouds
Current 3D single object tracking methods are typically based on VoteNet, a 3D region proposal network. Despite the success, using a single seed point feature as the cue for offset learning in VoteNet prevents high-quali…
3D Single Object TrackingObject TrackingRegion Proposal3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving Object
This paper aims to develop a multi-rotor-based visual tracker for a specified moving object. Visual object-tracking algorithms for multi-rotors are challenging due to multiple issues such as occlusion, quick camera motio…
3D Single Object TrackingDepth EstimationGPUObject+2CXTrack: 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+1OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds
Although recent Siamese network-based trackers have achieved impressive perceptual accuracy for single object tracking in LiDAR point clouds, they usually utilized heavy correlation operations to capture category-level c…
3D Single Object TrackingMultiple Object TrackingObject TrackingExploiting More Information in Sparse Point Cloud for 3D Single Object Tracking
3D single object tracking is a key task in 3D computer vision. However, the sparsity of point clouds makes it difficult to compute the similarity and locate the object, posing big challenges to the 3D tracker. Previous w…
3D Single Object TrackingDecoderObjectObject TrackingReal-time 3D Single Object Tracking with Transformer
LiDAR-based 3D single object tracking is a challenging issue in robotics and autonomous driving. Currently, existing approaches usually suffer from the problem that objects at long distance often have very sparse or part…
3D Single Object TrackingAutonomous DrivingGPUObject+1Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking
The point cloud based 3D single object tracking has drawn increasing attention. Although many breakthroughs have been achieved, we also reveal two severe issues. By extensive analysis, we find the prediction manner of cu…
3D Single Object TrackingObject TrackingPoint Cloud CompletionPrediction+13D Siamese Transformer Network for Single Object Tracking on Point Clouds
Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area. Due to the large appearance variation between the template and sear…
3D Single Object TrackingObject TrackingVPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
In this paper, we propose a novel voxel-based 3D single object tracking (3D SOT) method called Voxel Pseudo Image Tracking (VPIT). VPIT is the first method that uses voxel pseudo images for 3D SOT. The input point cloud …
3D Single Object TrackingObjectObject TrackingA Lightweight and Detector-free 3D Single Object Tracker on Point Clouds
Recent works on 3D single object tracking treat the task as a target-specific 3D detection task, where an off-the-shelf 3D detector is commonly employed for the tracking. However, it is non-trivial to perform accurate ta…
3D Single Object Trackingmotion predictionObject TrackingBeyond 3D Siamese Tracking: A Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
3D single object tracking (3D SOT) in LiDAR point clouds plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching. However, LiDAR point clouds are usuall…
3D Single Object TrackingAutonomous DrivingObject TrackingPTT: Point-Track-Transformer Module for 3D Single Object Tracking in Point Clouds
3D single object tracking is a key issue for robotics. In this paper, we propose a transformer module called Point-Track-Transformer (PTT) for point cloud-based 3D single object tracking. PTT module contains three blocks…
3D Single Object TrackingGPUObject TrackingPosition