Huawei Technologies Co., Limited

Xin Ding

Juwei Lu

Peng Dai

Xiaofei Wu

Deepak Sridhar

Sidharth Singla

Method and devices for training a keypoint estimation network are described. In each training iteration, synthetic images are generated by a generator, each synthetic image being assigned respective assigned keypoints by the generator. Using a prior-iteration of the keypoint estimation network, a set of predicted keypoints is obtained for each synthetic image. Based on an error score between the predicted keypoints and the assigned keypoints, poor quality synthetic images are discarded. The remaining synthetic images, together with real world images, are used to train an updated keypoint estimation network. The performance of the updated keypoint estimation network is validated, and the training iterations are performed until a convergence criteria is satisfied.

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Saint-Laurent, Canada

Xin Ding