FCPose

FCPose is a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions. Different from existing methods, which often require ROI (Region of Interest) operations and/or grouping post-processing, FCPose eliminates the ROIs and grouping pre-processing with dynamic instance aware keypoint estimation heads. The dynamic keypoint heads are conditioned on each instance (person), and can encode the instance concept in the dynamically-generated weights of their filters.

Overall, FCPose is built upon the one-stage object detector FCOS. The controller that generates the weights of the keypoint heads is attached to the FCOS heads. The weights θᵢ generated by the controller is used to fulfill the keypoint head f for the instance i. Moreover, a keypoint refinement module is introduced to predict the offsets from each location of the heatmaps to the ground-truth keypoints. Finally, the coordinates derived from the predicted heatmaps are refined by the offsets predicted by the keypoint refinement module, resulting in the final keypoint results. "Rel. coord." is a map of the relative coordinates from all the locations of the feature maps F to the location where the weights are generated. The relative coordinate map is concatenated to F as the input to the keypoint head.