Image-Text-to-Text
English
yahya007 commited on
Commit
4c0d303
Β·
verified Β·
1 Parent(s): 1f4c923

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +35 -31
README.md CHANGED
@@ -1,31 +1,35 @@
1
- # Visual Prompt Checkpoints for NR-IQA
2
-
3
- πŸ”¬ **Paper**: [Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA](https://arxiv.org/abs/xxxx.xxxxx)
4
- πŸ’» **Code**: [GitHub Repository](https://github.com/your-username/visual-prompt-nr-iqa)
5
-
6
- ## Overview
7
-
8
- Pre-trained visual prompt checkpoints for **No-Reference Image Quality Assessment (NR-IQA)** using mPLUG-Owl2-7B. Achieves competitive performance with only **~600K parameters** vs 7B+ for full fine-tuning.
9
-
10
- ## Available Checkpoints
11
-
12
- **Download**: `visual_prompt_ckpt_trained_on_mplug2.zip`
13
-
14
- | Dataset | SROCC | Experiment Folder |
15
- |---------|-------|-------------------|
16
- | KADID-10k | 0.932 | `SGD_mplug2_exp_04_kadid_padding_30px_add/` |
17
- | KonIQ-10k | 0.852 | `SGD_mplug2_exp_05_koniq_padding_30px_add/` |
18
- | AGIQA-3k | 0.810 | `SGD_mplug2_exp_06_agiqa_padding_30px_add/` |
19
-
20
- ## Citation
21
-
22
- ```bibtex
23
- @article{benmahane2024parameter,
24
- title={Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA},
25
- author={Benmahane, Yahya and El Hassouni, Mohammed},
26
- journal={arXiv preprint},
27
- year={2024}
28
- }
29
- ```
30
-
31
- **πŸ“– For detailed setup, training, and usage instructions, see the [GitHub repository](https://github.com/your-username/visual-prompt-nr-iqa).**
 
 
 
 
 
1
+ ---
2
+ datasets:
3
+ - chaofengc/IQA-PyTorch-Datasets
4
+ language:
5
+ - en
6
+ pipeline_tag: visual-question-answering
7
+ library_name: transformers
8
+ ---
9
+ # Visual Prompt Checkpoints for NR-IQA
10
+ πŸ”¬ **Paper**: [Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA](https://arxiv.org/abs/xxxx.xxxxx)
11
+ πŸ’» **Code**: [GitHub Repository](https://github.com/your-username/visual-prompt-nr-iqa)
12
+
13
+ ## Overview
14
+ Pre-trained visual prompt checkpoints for **No-Reference Image Quality Assessment (NR-IQA)** using mPLUG-Owl2-7B. Achieves competitive performance with only **~600K parameters** vs 7B+ for full fine-tuning.
15
+
16
+ ## Available Checkpoints
17
+ **Download**: `visual_prompt_ckpt_trained_on_mplug2.zip`
18
+
19
+ | Dataset | SROCC | Experiment Folder |
20
+ |---------|-------|-------------------|
21
+ | KADID-10k | 0.932 | `SGD_mplug2_exp_04_kadid_padding_30px_add/` |
22
+ | KonIQ-10k | 0.852 | `SGD_mplug2_exp_05_koniq_padding_30px_add/` |
23
+ | AGIQA-3k | 0.810 | `SGD_mplug2_exp_06_agiqa_padding_30px_add/` |
24
+
25
+ ## Citation
26
+ ```bibtex
27
+ @article{benmahane2024parameter,
28
+ title={Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA},
29
+ author={Benmahane, Yahya and El Hassouni, Mohammed},
30
+ journal={arXiv preprint},
31
+ year={2024}
32
+ }
33
+ ```
34
+
35
+ **πŸ“– For detailed setup, training, and usage instructions, see the [GitHub repository](https://github.com/your-username/visual-prompt-nr-iqa).**