RF-based Pose Estimation

3 papers with code • 1 benchmarks • 0 datasets

Detect human actions through walls and occlusions, and in poor lighting conditions. Taking radio frequency (RF) signals as input (e.g. Wifi), generating 3D human skeletons as an intermediate representation, and recognizing actions and interactions.

See e.g. RF-Pose from MIT for a good illustration of the approach http://rfpose.csail.mit.edu/

( Image credit: Making the Invisible Visible )

Most implemented papers

Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

hikvision-research/skelact 17 Apr 2018

Skeleton-based human action recognition has recently drawn increasing attentions with the availability of large-scale skeleton datasets.

Person-in-WiFi: Fine-grained Person Perception using WiFi

geekfeiw/wifiperson ICCV 2019

Fine-grained person perception such as body segmentation and pose estimation has been achieved with many 2D and 3D sensors such as RGB/depth cameras, radars (e. g., RF-Pose) and LiDARs.

Can WiFi Estimate Person Pose?

geekfeiw/WiSPPN 30 Mar 2019

In this paper We try to answer this question by exploring the ability of WiFi on estimating single person pose.