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RF-based Pose Estimation
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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/
<span style="color:grey; opacity: 0.6">( Image credit: Making the Invisible Visible )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Making the Invisible Visible: Action Recognition Through Walls and Occlusions
Milli-RIO: Ego-Motion Estimation with Millimetre-Wave Radar and Inertial Measurement Unit Sensor
Real Time 3D Indoor Human Image Capturing Based on FMCW Radar
A Survey on CSI-Based Human Behavior Recognition in Through-the-Wall Scenario
Person-in-WiFi: Fine-grained Person Perception using WiFi
Can WiFi Estimate Person Pose?
Light-Field for RF
AI-Enhanced 3D RF Representation Using Low-Cost mmWave Radar
RF-based 3D skeletons
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.