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MocapNET: Ensemble of SNN Encoders for 3D Human Pose Estimation in RGB Images
British Machine Vision Conference
We present MocapNET, an ensemble of SNN  encoders that estimates the 3D human body pose based on 2D joint estimations extracted from monocular RGB images. MocapNET provides an efficient divide and conquer strategy for supervised learning. It outputs skeletal information directly into the BVH  format which can be rendered in real-time or imported without any additional processing in most popular 3D animation software. The proposed architecture achieves 3D human pose estimations at statedblp:conf/bmvc/QammazA19 fatcat:wo2h6omfdzbwjmbwucsgd7qopy