Segment and Caption Anything

1. Despite the absence of semantic labels in the training data, SAM implies high-level semantics sufficient for captioning.
2. SCA (b) is a lightweight augmentation of SAM (a) with the ability to generate regional captions.
3. On top of SAM architecture, we add a fixed pre-trained language mode, and a optimizable lightweight hybrid feature mixture whose training is cheap and scalable.

• [01/31/2024] Update the paper and the supp. Release code v0.0.2: bump transformers to 4.36.2, support mistral series, phi-2, zephyr; add experiments about SAM+Image Captioner+V-CoT, and more.
• [12/05/2023] Release paper, code v0.0.1, and project page!

Environment Preparation

Model Zoo

Gradio Demo

Running Training and Inference

Experiments and Evaluation

License

Acknowledgement

Citation

@misc{xiaoke2023SCA,
  title={{Segment and Caption Anything}},
  author={Xiaoke, Huang and Jianfeng, Wang and Yansong, Tang and Zheng, Zhang and Han, Hu and Jiwen, Lu and Lijuan, Wang and Zicheng, Liu},
  journal={arXiv},
  volume={abs/2312.00869},
  year={2023},
}