Pose Prediction
57 papers with code • 3 benchmarks • 8 datasets
Pose prediction is to predict future poses given a window of previous poses.
Benchmarks
These leaderboards are used to track progress in Pose Prediction
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Datasets
NTU RGB+D
G3D
Expi
SportsPose
Drunkard's Dataset
InfiniteRep
Latest papers
KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D input
ivalab/kgn
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We propose a new 6-DoF grasp pose synthesis approach from 2D/2. 5D input based on keypoints.
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction
Predicting the pose of objects from a single image is an important but difficult computer vision problem.
Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE
Here, we consider the problem of learning semantic representations of objects that are invariant to pose and location in a fully unsupervised manner.
A generic diffusion-based approach for 3D human pose prediction in the wild
Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions.
SPARC: Sparse Render-and-Compare for CAD model alignment in a single RGB image
This combined information is the input to a pose prediction network, SPARC-Net which we train to predict a 9 DoF CAD model pose update.
LATITUDE: Robotic Global Localization with Truncated Dynamic Low-pass Filter in City-scale NeRF
jike5/LATITUDE
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In this paper, we present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter, which introduces a two-stage localization mechanism in city-scale NeRF.
STPOTR: Simultaneous Human Trajectory and Pose Prediction Using a Non-Autoregressive Transformer for Robot Following Ahead
The proposed architecture divides human motion prediction into two parts: 1) the human trajectory, which is the hip joint 3D position over time and 2) the human pose which is the all other joints 3D positions over time with respect to a fixed hip joint.
Uni-Mol: A Universal 3D Molecular Representation Learning Framework
dptech-corp/Uni-Mol
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ChemRxiv 2022
Uni-Mol is composed of two models with the same SE(3)-equivariant transformer architecture: a molecular pretraining model trained by 209M molecular conformations; a pocket pretraining model trained by 3M candidate protein pocket data.
3D Textured Shape Recovery with Learned Geometric Priors
3D textured shape recovery from partial scans is crucial for many real-world applications.
PoseBERT: A Generic Transformer Module for Temporal 3D Human Modeling
naver/posebert
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It is simple, generic and versatile, as it can be plugged on top of any image-based model to transform it in a video-based model leveraging temporal information.
