dgjun32 / RPO

Official Implementation of "Read-only Prompt Optimization for Vision-Language Few-shot Learning", ICCV 2023

Read-only-Prompt-Optimization for Vision-Language Few-shot Learning

This is the official implementation of the ICCV 2023 paper, "Read-only Prompt Optimization for Vision-Language Few-shot Learning" by D. Lee, S. Song, J. Suh, J. Choi, S. Lee and H. J. Kim.

1. Setup & Installations

1. install Dassl library following instruction from this link (For reproduction, cuda version 11.7 is recommended.)
2. Follow DATASET.md to download datasets under data/ directory.

2. How to Run Experiments?

2.1. Data path setup

For every base2new_train.sh, base2new_test.sh, xd_train.sh, and xd_test.sh file in scripts/*/ directory, uncomment DATA= and insert the current data directory (e.g., DATA=data/) in the field.

2.2. Using Checkpoint

If you want to check reproducibility of Table1 and Table2, without multiple times of time-consuming training, you may download rpo.zip file from this link, unzip the file and place it under the output/ directory.

2.3. Run Experiments

Table 1. Base to new generalization

# Linear Probe
sh scripts/lp/base2new_generalization_main.sh [gpu_id]

# CoOp
sh scripts/coop/base2new_generalization_main.sh [gpu_id]

# CoCoOp
sh scripts/cocoop/base2new_generalization_main.sh [gpu_id]

# RPO
sh scripts/rpo/base2new_generalization_main.sh [gpu_id]

Table 2. Domain generalization

# CoOp
sh scripts/coop/domain_generalization_main.sh [gpu_id]

# CoCoOp
sh scripts/cocoop/domain_generalization_main.sh [gpu_id]

# RPO
sh scripts/rpo/domain_generalization_main.sh [gpu_id]

Analyes & Figures

Figure 1.

# CoOp
sh scripts/coop/motivation.sh [gpu_id]

# CoCoOp
sh scripts/cocoop/motivation.sh [gpu_id]

# Linear Probe
sh scripts/lp/motivation.sh [gpu_id]

Table 4 & Figure 5

# RPO
sh scripts/rpo/efs_base2new_generalization_main.sh [gpu_id]

# CoCoOp
sh scripts/cocoop/efs_base2new_generalization_main.sh [gpu_id]

Citation

@inproceedings{lee2023rpo,
  title={Read-only Prompt Optimization for Vision-Language Few-shot Learning},
  author={Lee, Dongjun and Song, Seokwon and Suh, Jihee and Choi, Joonmyeong and Lee, Sanghyeok and Kim, Hyunwoo J.},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2023}
}

License

Licensed under MIT License

• Copyright (c) 2022 MLV Lab (Machine Learning and Vision Lab at Korea University)