Semi-Supervised and Long-Tailed Object Detection with CascadeMatch

Author:

Zang YuhangORCID,Zhou Kaiyang,Huang Chen,Loy Chen Change

Funder

Singapore MOE AcRF Tier 2

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference92 articles.

1. Arazo, E., Ortego, D., Albert, P., O’Connor, N. E. & McGuinness, K. (2020). Pseudo-labeling and confirmation bias in deep semi-supervised learning. In IJCNN.

2. Bachman, P., Alsharif, O. & Precup, D. (2014). Learning with pseudo-ensembles. In NeurIPS.

3. Berthelot, D., Carlini, N., Goodfellow, I., Papernot, N., Oliver, A. & Raffel, C. (2019). MixMatch: a holistic approach to semi-supervised learning. In NeurIPS.

4. Berthelot, D., Carlini, N., Cubuk, E. D., Kurakin, A., Sohn, K., Zhang, H. & Raffel, C. (2020). Remixmatch: semi-supervised learning with distribution alignment and augmentation anchoring. In ICLR.

5. Cai, Z. & Vasconcelos, N. (2019). Cascade R-CNN: high quality object detection and instance segmentation. TPAMI.

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