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Found 4 papers, 4 papers with code
Simultaneous Multiple Object Detection and Pose Estimation using 3D Model Infusion with Monocular Vision
Using the labeling method, we provide the KITTI-6DoF dataset with $\sim7. 5$K annotated frames.
Simultaneous Detection and Tracking with Motion Modelling for Multiple Object Tracking
Deep learning-based Multiple Object Tracking (MOT) currently relies on off-the-shelf detectors for tracking-by-detection. This results in deep models that are detector biased and evaluations that are detector influenced.
Deep Affinity Network for Multiple Object Tracking
In this paper, we harness the power of deep learning for data association in tracking by jointly modelling object appearances and their affinities between different frames in an end-to-end fashion.
Benchmark data and method for real-time people counting in cluttered scenes using depth sensors
A thorough evaluation on PCDS demonstrates that our technique is able to count people in cluttered scenes with high accuracy at 45 fps on a 1. 7 GHz processor, and hence it can be deployed for effective real-time people counting for intelligent transportation systems.
