Vehicle Pose Estimation
17 papers with code • 4 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Vehicle Pose Estimation
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KITTI
ApolloCar3D
CarFusion
Most implemented papers
3D Bounding Box Estimation Using Deep Learning and Geometry
smallcorgi/3D-Deepbox
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CVPR 2017
In contrast to current techniques that only regress the 3D orientation of an object, our method first regresses relatively stable 3D object properties using a deep convolutional neural network and then combines these estimates with geometric constraints provided by a 2D object bounding box to produce a complete 3D bounding box.
M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
garrickbrazil/M3D-RPN
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ICCV 2019
Understanding the world in 3D is a critical component of urban autonomous driving.
Learning Depth-Guided Convolutions for Monocular 3D Object Detection
3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information.
RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving
Banconxuan/RTM3D
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ECCV 2020
Different from these approaches, our method predicts the nine perspective keypoints of a 3D bounding box in image space, and then utilize the geometric relationship of 3D and 2D perspectives to recover the dimension, location, and orientation in 3D space.
Kinematic 3D Object Detection in Monocular Video
Nicholasli1995/EgoNet
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ECCV 2020
In this work, we propose a novel method for monocular video-based 3D object detection which carefully leverages kinematic motion to improve precision of 3D localization.
Subcategory-aware Convolutional Neural Networks for Object Proposals and Detection
In CNN-based object detection methods, region proposal becomes a bottleneck when objects exhibit significant scale variation, occlusion or truncation.
BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance
We also show that our method outperforms the state-of-the-art methods for fine-grained recognition.
Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstruction
We present MonoPSR, a monocular 3D object detection method that leverages proposals and shape reconstruction.
Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks
dineshreddy91/Occlusion_Net
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CVPR 2019
Central to this work is a trifocal tensor loss that provides indirect self-supervision for occluded keypoint locations that are visible in other views of the object.
6D-VNet: End-to-end 6DoF Vehicle Pose Estimation from Monocular RGB Images
stevenwudi/6DVNET
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The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019 2019
We present a conceptually simple framework for 6DoF object pose estimation, especially for autonomous driving scenario.
