Pose Retrieval
9 papers with code • 2 benchmarks • 2 datasets
Retrieval of similar human poses from images or videos
Human3.6M
MPI-INF-3DHP
Latest papers with no code
Normalized Human Pose Features for Human Action Video Alignment
We present a novel approach for extracting human pose features from human action videos.
I Like to Move It: 6D Pose Estimation as an Action Decision Process
We change this paradigm and reformulate the problem as an action decision process where an initial pose is updated in incremental discrete steps that sequentially move a virtual 3D rendering towards the correct solution.
Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation
The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly and require sophisticated systems to acquire.
RelocNet: Continuous Metric Learning Relocalisation using Neural Nets
We propose a method of learning suitable convolutional representations for camera pose retrieval based on nearest neighbour matching and continuous metric learning-based feature descriptors.
LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization
We propose LandmarkBoost - an approach that, in contrast to the conventional 2D-3D matching methods, casts the search problem as a landmark classification task.
When Regression Meets Manifold Learning for Object Recognition and Pose Estimation
By combining the strengths of manifold learning using triplet loss and pose regression, we could either estimate the pose directly reducing the complexity compared to NN search, or use learned descriptor for the NN descriptor matching.
A Dual-Source Approach for 3D Human Pose Estimation from a Single Image
To this end, we first convert the motion capture data into a normalized 2D pose space, and separately learn a 2D pose estimation model from the image data.
Learning Robust Hash Codes for Multiple Instance Image Retrieval
In this paper, for the first time, we introduce a multiple instance (MI) deep hashing technique for learning discriminative hash codes with weak bag-level supervision suited for large-scale retrieval.
A Dual-Source Approach for 3D Pose Estimation from a Single Image
To integrate both sources, we propose a dual-source approach that combines 2D pose estimation with efficient and robust 3D pose retrieval.
