3D Single Object Tracking
22 papers with code • 0 benchmarks • 1 datasets
3D tracking of a single object, based on an initial 3D bounding box, provided to the tracker. 3D single object tracking is commonly performed using point cloud data from Lidars, as it provides valuable depth information, which is lost in camera images. However, irregular point cloud structure and an increasing point sparsity with distance makes Lidar-based 3D single object tracking a nontrivial task.
Benchmarks
These leaderboards are used to track progress in 3D Single Object Tracking
Libraries
Use these libraries to find 3D Single Object Tracking models and implementations
KITTI
Most implemented papers
3D Siamese Transformer Network for Single Object Tracking on Point Clouds
fpthink/stnet
•
•
Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area.
Real-time 3D Single Object Tracking with Transformer
shanjiayao/ptt
•
•
PTT module in the voting stage could model the interactions among point patches, which learns context-dependent features.
Exploiting More Information in Sparse Point Cloud for 3D Single Object Tracking
3bobo/smat
•
•
Meanwhile, the encoder applies the attention on multi-scale features to compensate for the lack of information caused by the sparsity of point cloud and the single scale of features.
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving Object
mhd-medfa/Single-Object-Tracker
•
•
Remote Sensing 2022
According to the experiment results, the class-specific object tracker performed better than the generic object tracker in terms of stability and accuracy.
MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency
mumuqiao/mixcycle
•
•
ICCV 2023
Specifically, we introduce two cycle-consistency strategies for supervision: 1) Self tracking cycles, which leverage labels to help the model converge better in the early stages of training; 2) forward-backward cycles, which strengthen the tracker's robustness to motion variations and the template noise caused by the template update strategy.
An Effective Motion-Centric Paradigm for 3D Single Object Tracking in Point Clouds
Due to the motion-centric nature, our method shows its impressive generalizability with limited training labels and provides good differentiability for end-to-end cycle training.
GLT-T++: Global-Local Transformer for 3D Siamese Tracking with Ranking Loss
haooozi/glt-t
•
•
Incorporating this transformer-based voting scheme into 3D RPN, a novel Siamese method dubbed GLT-T is developed for 3D single object tracking on point clouds.
MMF-Track: Multi-modal Multi-level Fusion for 3D Single Object Tracking
To overcome the limitations of geometry matching, we propose a Multi-modal Multi-level Fusion Tracker (MMF-Track), which exploits the image texture and geometry characteristic of point clouds to track 3D target.
Motion-to-Matching: A Mixed Paradigm for 3D Single Object Tracking
3D single object tracking with LiDAR points is an important task in the computer vision field.
BEVTrack: A Simple and Strong Baseline for 3D Single Object Tracking in Bird's-Eye View
The spatial information indicating objects' spatial adjacency across consecutive frames is crucial for effective object tracking.
