6D Pose Estimation using RGBD
26 papers with code • 8 benchmarks • 6 datasets
Image: Zeng et al
Benchmarks
These leaderboards are used to track progress in 6D Pose Estimation using RGBD
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Libraries
Use these libraries to find 6D Pose Estimation using RGBD models and implementations
YCB-Video
T-LESS
REAL275
6IMPOSE
Drunkard's Dataset
Most implemented papers
ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization
A novel disentangled shape and appearance database of priors is first learned to embed objects in their respective shape and appearance space.
BOP: Benchmark for 6D Object Pose Estimation
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image.
MaskedFusion: Mask-based 6D Object Pose Estimation
MaskedFusion is a framework to estimate the 6D pose of objects using RGB-D data, with an architecture that leverages multiple sub-tasks in a pipeline to achieve accurate 6D poses.
Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands
The hand's point cloud is pruned and robust global registration is performed to generate object pose hypotheses, which are clustered.
EPOS: Estimating 6D Pose of Objects with Symmetries
thodan/epos
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CVPR 2020
A data-dependent number of corresponding 3D locations is selected per pixel, and poses of possibly multiple object instances are estimated using a robust and efficient variant of the PnP-RANSAC algorithm.
DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency
Gorilla-Lab-SCUT/DualPoseNet
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ICCV 2021
DualPoseNet stacks two parallel pose decoders on top of a shared pose encoder, where the implicit decoder predicts object poses with a working mechanism different from that of the explicit one; they thus impose complementary supervision on the training of pose encoder.
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for fewer, more disperse keypoints.
BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
Most prior efforts, however, often assume that the target object's CAD model, at least at a category-level, is available for offline training or during online template matching.
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
Drawing inspirations from traditional point pair features (PPFs), in this paper, we design a novel Category-level PPF (CPPF) voting method to achieve accurate, robust and generalizable 9D pose estimation in the wild.
Iterative Corresponding Geometry: Fusing Region and Depth for Highly Efficient 3D Tracking of Textureless Objects
Tracking objects in 3D space and predicting their 6DoF pose is an essential task in computer vision.
