• Corpus ID: 244709355

VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition

@article{Tian2021VLLTRLC,
  title={VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition},
  author={Changyao Tian and Wenhai Wang and Xizhou Zhu and Xiaogang Wang and Jifeng Dai and Y. Qiao},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.13579}
}
Deep learning-based models encounter challenges when processing long-tailed data in the real world. Existing solutions usually employ some balancing strategies or transfer learning to deal with the class imbalance problem, based on the image modality. In this work, we present a visuallinguistic long-tailed recognition framework, termed VLLTR, and conduct empirical studies on the benefits of introducing text modality for long-tailed recognition (LTR). Compared to existing approaches, the… 

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