Associative Embedding: End-to-End Learning for Joint Detection and Grouping

@inproceedings{Newell2017AssociativeEE,
  title={Associative Embedding: End-to-End Learning for Joint Detection and Grouping},
  author={Alejandro Newell and Zhiao Huang and Jia Deng},
  booktitle={NIPS},
  year={2017}
}
We introduce associative embedding, a novel method for supervising convolutional neural networks for the task of detection and grouping. A number of computer vision problems can be framed in this manner including multi-person pose estimation, instance segmentation, and multi-object tracking. Usually the grouping of detections is achieved with multi-stage pipelines, instead we propose an approach that teaches a network to simultaneously output detections and group assignments. This technique can… CONTINUE READING

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