Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing

@article{Gong2017LookIP,
  title={Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing},
  author={Ke Gong and Xiaodan Liang and Xiaohui Shen and Liang Lin},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={6757-6765}
}
Human parsing has recently attracted a lot of research interests due to its huge application potentials. However existing datasets have limited number of images and annotations, and lack the variety of human appearances and the coverage of challenging cases in unconstrained environment. In this paper, we introduce a new benchmark Look into Person (LIP) that makes a significant advance in terms of scalability, diversity and difficulty, a contribution that we feel is crucial for future… CONTINUE READING
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