3D Pose Estimation
133 papers with code • 6 benchmarks • 30 datasets
Benchmarks
These leaderboards are used to track progress in 3D Pose Estimation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find 3D Pose Estimation models and implementations
Human3.6M
LSP
HO-3D
Hypersim
MuCo-3DHP
ApolloCar3D
SVIRO
Unite the People
CarFusion
Most implemented papers
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose
google-research/google-research
•
•
Recognition of human poses and actions is crucial for autonomous systems to interact smoothly with people.
Heuristic Weakly Supervised 3D Human Pose Estimation
However, recent models depend on supervised training with 3D pose ground truth data or known pose priors for their target domains.
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
google-research/google-research
•
•
Single image pose estimation is a fundamental problem in many vision and robotics tasks, and existing deep learning approaches suffer by not completely modeling and handling: i) uncertainty about the predictions, and ii) symmetric objects with multiple (sometimes infinite) correct poses.
Direct Multi-view Multi-person 3D Pose Estimation
Instead of estimating 3D joint locations from costly volumetric representation or reconstructing the per-person 3D pose from multiple detected 2D poses as in previous methods, MvP directly regresses the multi-person 3D poses in a clean and efficient way, without relying on intermediate tasks.
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
With a simple yet effective motion-aware fully-connected network, SmoothNet improves the temporal smoothness of existing pose estimators significantly and enhances the estimation accuracy of those challenging frames as a side-effect.
Graph Neural Networks for Cross-Camera Data Association
To avoid the usage of fixed distances, we leverage the connectivity of Graph Neural Networks, previously unused in this scope, using a Message Passing Network to jointly learn features and similarity.
Visual Pursuit Control based on Gaussian Processes with Switched Motion Trajectories
This paper considers a scenario of pursuing a moving target that may switch behaviors due to external factors in a dynamic environment by motion estimation using visual sensors.
EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams
In response to the existing limitations, this paper 1) introduces a new problem, i. e., 3D human motion capture from an egocentric monocular event camera with a fisheye lens, and 2) proposes the first approach to it called EventEgo3D (EE3D).
Globally Tuned Cascade Pose Regression via Back Propagation with Application in 2D Face Pose Estimation and Heart Segmentation in 3D CT Images
We empirically show that global training with BP outperforms layer-wise (pre-)training.
Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video
chuxiaoselena/SparsenessMeetsDeepness
•
•
CVPR 2016
Here, two cases are considered: (i) the image locations of the human joints are provided and (ii) the image locations of joints are unknown.
