├── figures └── CoPS_schematic.png ├── LICENSE ├── README.md └── .gitignore /figures/CoPS_schematic.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/cqylunlun/CoPS/HEAD/figures/CoPS_schematic.png -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2025 Qiyu Chen 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # CoPS 2 | 3 | ![](figures/CoPS_schematic.png) 4 | 5 | **CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection** 6 | 7 | _Qiyu Chen, Zhen Qu, Wei Luo, Haiming Yao, Yunkang Cao, Yuxin Jiang, Yinan Duan, 8 | Huiyuan Luo, Chengkan Lv*, Zhengtao Zhang_ 9 | 10 | [ArXiv Preprint Link](https://arxiv.org/abs/2508.03447) 11 | 12 | ## Introduction 13 | CoPS dynamically synthesizes visually conditioned prompts to fine‑tune CLIP, achieving SOTA zero‑shot anomaly detection. 14 | The source code and model checkpoints for CoPS will be released upon the paper’s acceptance. Stay tuned. 15 | Here, we present a brief summary of CoPS's performance across 5 industrial and 8 medical datasets: 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 |

Metrics	MVTec-AD	VisA	BTAD	MPDD	DTD-Synthetic	HeadCT	BrainMRI	Br35H	ISIC	CVC-ColonDB	CVC-ClinicDB	Kvasir	Endo
I-AUROC (%)	95.0	85.4	93.6	78.6	95.2	96.1	97.4	98.7	–	–	–	–	–
P-AUROC (%)	93.4	95.7	94.6	97.5	98.4	–	–	–	93.8	85.6	88.8	85.8	90.0

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