Vehicle Pose Estimation
19 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
DSGN: Deep Stereo Geometry Network for 3D Object Detection
chenyilun95/DSGN
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CVPR 2020
Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.
MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationships
Nicholasli1995/EgoNet
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CVPR 2020
Monocular 3D object detection is an essential component in autonomous driving while challenging to solve, especially for those occluded samples which are only partially visible.
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
In this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images.
GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision
lkeab/gsnet
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ECCV 2020
GSNet utilizes a unique four-way feature extraction and fusion scheme and directly regresses 6DoF poses and shapes in a single forward pass.
Exploring intermediate representation for monocular vehicle pose estimation
Nicholasli1995/EgoNet
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CVPR 2021
The latter question motivates us to incorporate geometry knowledge with a new loss function based on a projective invariant.
Optimal Pose and Shape Estimation for Category-level 3D Object Perception
Our first contribution is to provide the first certifiably optimal solver for pose and shape estimation.
Optimal and Robust Category-level Perception: Object Pose and Shape Estimation from 2D and 3D Semantic Keypoints
We consider an active shape model, where -- for an object category -- we are given a library of potential CAD models describing objects in that category, and we adopt a standard formulation where pose and shape are estimated from 2D or 3D keypoints via non-convex optimization.
An Efficient Convex Hull-based Vehicle Pose Estimation Method for 3D LiDAR
In this paper, we propose a novel vehicle pose estimation method based on the convex hull.
Pose Anything: A Graph-Based Approach for Category-Agnostic Pose Estimation
This approach not only enables object pose generation based on arbitrary keypoint definitions but also significantly reduces the associated costs, paving the way for versatile and adaptable pose estimation applications.
