FaceRSA: RSA-Aware Facial Identity Cryptography Framework
Authors: Zhongyi Zhang, Tianyi Wei, Wenbo Zhou, Hanqing Zhao, Weiming Zhang, Nenghai Yu
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments and ablation analyses demonstrate the superiority of our method in terms of the quality of synthesis results, identity-irrelevant attributes preservation, deanonymization accuracy, and completeness of properties analogous to RSA. |
| Researcher Affiliation | Academia | University of Science and Technology of China {ericzhang@mail., bestwty@mail., welbeckz@, zhq2015@mail., zhangwm@, ynh@}ustc.edu.cn |
| Pseudocode | No | The paper describes the methodology in text and figures but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code or a direct link to a code repository for the methodology described. |
| Open Datasets | No | The paper does not provide concrete access information (specific link, DOI, repository name, formal citation with authors/year) for a publicly available or open dataset used for training, nor does it explicitly name one of the well-known public datasets in the context of its experiments. |
| Dataset Splits | No | The paper mentions that implementation details are in the supplementary material, but the main text does not provide specific dataset split information (exact percentages, sample counts, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper mentions using specific models like Style GAN and Arcface, but it does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | No | The paper states that 'The detailed designs and the hyperparameter settings of Lsingle, Lseq and Lasso are presented in the supplementary material', implying that these details are not in the main text. |