Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds
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- Type
- preprint
- Published
- 2019-04-16
- Cited by
- 229
- References
- 48
- Access
- Open access
- OpenAlex
- https://openalex.org/W2940208651
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:119181576
Keywords
Computer science, Artificial intelligence, Computer vision, Object detection, Inference
References
- EKF/UKF maneuvering target tracking using coordinated turn models with polar/Cartesian velocity
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- Learning Spatiotemporal Features with 3D Convolutional Networks
- FollowMe: Efficient Online Min-Cost Flow Tracking with Bounded Memory and Computation
- The Labeled Multi-Bernoulli Filter
- A random finite set conjugate prior and application to multi-target tracking
- Are we ready for autonomous driving? The KITTI vision benchmark suite
- Deep Residual Learning for Image Recognition
- SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size
- The Cityscapes Dataset for Semantic Urban Scene Understanding
- ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
- 3D Object Proposals Using Stereo Imagery for Accurate Object Class Detection
- Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks
- Multi-view 3D Object Detection Network for Autonomous Driving
- 3D fully convolutional network for vehicle detection in point cloud
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
- Feature Pyramid Networks for Object Detection
- YOLO9000: Better, Faster, Stronger
Cited by
- Real-time Dynamic Object Detection for Autonomous Driving using Prior 3D-Maps
- A Baseline for 3D Multi-Object Tracking
- Vehicular Multi-object Tracking with Persistent Detector Failures
- Robust visual tracking based on variational auto-encoding Markov chain Monte Carlo
- Deep Learning on Point Clouds and Its Application: A Survey
- Real-time Detection and Tracking of Moving Objects Using Deep Learning and Multi-threaded Kalman Filtering : A joint solution of 3D object detection and tracking for Autonomous Driving
- Deep SCNN-Based Real-Time Object Detection for Self-Driving Vehicles Using LiDAR Temporal Data
- Oracle bone inscription detection: a survey of Oracle bone inscription detection based on deep learning algorithm
- Fusion of 3D LIDAR and Camera Data for Object Detection in Autonomous Vehicle Applications
- Cascaded Sliding Window Based Real-Time 3D Region Proposal for Pedestrian Detection*
- StickyPillars: Robust feature matching on point clouds using Graph Neural Networks
- PointTrackNet: An End-to-End Network For 3-D Object Detection and Tracking From Point Clouds
- 3D Object Detection From LiDAR Data Using Distance Dependent Feature Extraction
- BirdNet+: End-to-End 3D Object Detection in LiDAR Bird’s Eye View
- Joint 3D Tracking and Forecasting with Graph Neural Network and Diversity Sampling
- A Multi Sensor Real-time Tracking with LiDAR and Camera
- DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes
- Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review
- TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
- HKSiamFC: Visual-Tracking Framework Using Prior Information Provided by Staple and Kalman Filter
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