vehicle detection
54 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in vehicle detection
Most implemented papers
Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection
tensorflow/models
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CVPR 2020
In this paper we propose a method that leverages temporal context from the unlabeled frames of a novel camera to improve performance at that camera.
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery
This paper presents a framework for extracting georeferenced vehicle trajectories from high-altitude drone footage, addressing key challenges in urban traffic monitoring and limitations of traditional ground-based systems.
Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?
umautobots/driving-in-the-matrix
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Deep learning has rapidly transformed the state of the art algorithms used to address a variety of problems in computer vision and robotics.
DroNet: Efficient convolutional neural network detector for real-time UAV applications
Through the analysis we propose a CNN architecture that is capable of detecting vehicles from aerial UAV images and can operate between 5-18 frames-per-second for a variety of platforms with an overall accuracy of ~95%.
PIXOR: Real-time 3D Object Detection from Point Clouds
DerrickXuNu/OpenCOOD
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CVPR 2018
Existing approaches are, however, expensive in computation due to high dimensionality of point clouds.
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning
To address this dilemma, we further propose an uncertainty-aware cross-modality vehicle detection (UA-CMDet) framework to extract complementary information from cross-modal images, which can significantly improve the detection performance in low light conditions.
Vehicle Detection in Aerial Imagery (VEDAI) : a benchmark
mr8bit/vedai
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Journal of Visual Communication and Image Representation 2015
VEDAI is a dataset for Vehicle Detection in Aerial Imagery, provided as a tool to benchmark automatic target recognition algorithms in unconstrained environments.
3D Fully Convolutional Network for Vehicle Detection in Point Cloud
yukitsuji/3D_CNN_tensorflow
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2D fully convolutional network has been recently successfully applied to object detection from images.
Understanding Traffic Density from Large-Scale Web Camera Data
polltooh/traffic_video_analysis
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CVPR 2017
Understanding traffic density from large-scale web camera (webcam) videos is a challenging problem because such videos have low spatial and temporal resolution, high occlusion and large perspective.
Joint Monocular 3D Vehicle Detection and Tracking
ucbdrive/3d-vehicle-tracking
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ICCV 2019
The framework can not only associate detections of vehicles in motion over time, but also estimate their complete 3D bounding box information from a sequence of 2D images captured on a moving platform.
