Bi-calibration Networks for Weakly-Supervised Video Representation Learning

Author:

Long Fuchen,Yao TingORCID,Qiu Zhaofan,Tian Xinmei,Luo Jiebo,Mei Tao

Funder

National Key R &D Program of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference113 articles.

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2. Agrawal, P., Carreira, J., & Malik, J. (2015). Learning to see by moving. In ICCV.

3. Alwassel, H., Mahajan, D., Korbar, B., Torresani, L., Ghanem, B., & Tran, D. (2020). Self-supervised learning by cross-modal audio-video clustering. In NeurIPS.

4. Arnab, A., Dehghani, M., Heigold, G., Sun, C., Lucic, M., & Schmid, C. (2021). ViViT: A video vision transformer. In ICCV.

5. Avila, S., Thome, N., Cord, M., & Valle, E. (2013). de A Araujo A. The visual codeword point of view. Compute vision and image understanding: Pooling in image representation.

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