Efficient Modeling of Future Context for Image Captioning

Author:

Fei Zhengcong1

Affiliation:

1. Meituan, Beijing, China

Publisher

ACM

Reference67 articles.

1. Almost Free Semantic Draft for Neural Machine Translation

2. SPICE: Semantic Propositional Image Caption Evaluation

3. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

4. Dzmitry Bahdanau , Kyunghyun Cho , and Yoshua Bengio . 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 ( 2014 ). Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).

5. Manuele Barraco , Matteo Stefanini , Marcella Cornia , Silvia Cascianelli , Lorenzo Baraldi , and Rita Cucchiara . 2022. CaMEL: Mean Teacher Learning for Image Captioning. arXiv preprint arXiv:2202.10492 ( 2022 ). Manuele Barraco, Matteo Stefanini, Marcella Cornia, Silvia Cascianelli, Lorenzo Baraldi, and Rita Cucchiara. 2022. CaMEL: Mean Teacher Learning for Image Captioning. arXiv preprint arXiv:2202.10492 (2022).

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