Car Pose Estimation
4 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Convolutional Pose Machines
Pose Machines provide a sequential prediction framework for learning rich implicit spatial models.
OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.
Keypoint Communities
We present a fast bottom-up method that jointly detects over 100 keypoints on humans or objects, also referred to as human/object pose estimation.
Edge Weight Prediction For Category-Agnostic Pose Estimation
Category-Agnostic Pose Estimation (CAPE) localizes keypoints across diverse object categories with a single model, using one or a few annotated support images.