| 研究実績の概要 |
We expand our knowledge of the cross-modality between vision and language spaces. We obtained four achievements:
1. By using commonsense knowledge, we can anticipate the future, given a set of sparsely temporally-ordered set of images. It was published at CVPR 2023.
2. We explore training GANs under limited and open-set dataset as well as GAN inversion. The three papers were published at WACV 2024.
3. We build a new knowledge containing image features and corresponding object names. Using it, we propose a method for novel object captioning that outperforms other methods while being comparable to LLMs. It will be published at CVPR 2024.
4. We also gain knowledge about bias mitigation in image classification using a mixture of biases-specific experts. It was published at ICCV 2023.
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