CASIA-SURF_CeFA:面部反欺骗攻击检测挑战@ CVPR2020-源码

上传者: 42107491 | 上传时间: 2021-06-18 22:47:10 | 文件大小: 3.15MB | 文件类型: ZIP
Chalearn CeFA面对反欺骗挑战 这是我们在CVPR 2020上针对Chalearn单模式人脸防欺骗攻击检测挑战的解决方案的代码。 如果您在实验中使用此代码,请访问以下论文: : 我们的解决方案基于两种类型的人工变换:秩合并[1]和光流[2],并在端到端流水线中组合以进行欺骗检测和序列增强,以丰富伪造轨道的集合。 参考 [1] Basura Fernando,Efstratios Gavves,Jose Oramas,AmirGhodrati和Tinne Tuytelaars。进行行动识别的排名汇总。TPAMI,39(4):773–787,201 [2] C. Liu。 超越像素:探索运动分析的新表示形式和应用。 博士论文。 麻省理工学院,2009。 训练步骤 步骤1。 安装at_learner_core cd /path/to/new/pip/environment

文件下载

资源详情

[{"title":"( 75 个子文件 3.15MB ) CASIA-SURF_CeFA:面部反欺骗攻击检测挑战@ CVPR2020-源码","children":[{"title":"CASIA-SURF_CeFA-master","children":[{"title":"at_learner_core","children":[{"title":"at_learner_core","children":[{"title":"predictor.py <span style='color:#111;'> 2.86KB </span>","children":null,"spread":false},{"title":"configs.py <span style='color:#111;'> 4.41KB </span>","children":null,"spread":false},{"title":"models","children":[{"title":"init_model.py <span style='color:#111;'> 393B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 35B </span>","children":null,"spread":false},{"title":"model.py <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"architectures","children":[{"title":"resnet.py <span style='color:#111;'> 7.50KB </span>","children":null,"spread":false},{"title":"simplenet.py <span style='color:#111;'> 2.51KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 2.24KB </span>","children":null,"spread":false},{"title":"mobilenetv2.py <span style='color:#111;'> 5.42KB </span>","children":null,"spread":false},{"title":"efficientnet.py <span style='color:#111;'> 19.71KB </span>","children":null,"spread":false}],"spread":true},{"title":"wrappers","children":[{"title":"simple_classifier_wrapper.py <span style='color:#111;'> 1.77KB </span>","children":null,"spread":false},{"title":"losses.py <span style='color:#111;'> 1.36KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 62B </span>","children":null,"spread":false},{"title":"wrapper.py <span style='color:#111;'> 576B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"loggers","children":[{"title":"logger_manager.py <span style='color:#111;'> 1.03KB </span>","children":null,"spread":false},{"title":"logger.py <span style='color:#111;'> 234B </span>","children":null,"spread":false},{"title":"tensorboard_logger.py <span style='color:#111;'> 2.78KB </span>","children":null,"spread":false},{"title":"combine_logger.py <span style='color:#111;'> 742B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"terminal_logger.py <span style='color:#111;'> 5.69KB </span>","children":null,"spread":false},{"title":"file_logger.py <span style='color:#111;'> 1.18KB </span>","children":null,"spread":false}],"spread":true},{"title":"config_doc.md <span style='color:#111;'> 2.97KB </span>","children":null,"spread":false},{"title":"test_config.py <span style='color:#111;'> 913B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 36B </span>","children":null,"spread":false},{"title":"trainer.py <span style='color:#111;'> 6.51KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 23B </span>","children":null,"spread":false},{"title":"__version__.py <span style='color:#111;'> 22B </span>","children":null,"spread":false},{"title":"utils","children":[{"title":"transforms.py <span style='color:#111;'> 20.57KB </span>","children":null,"spread":false},{"title":"meters.py <span style='color:#111;'> 5.48KB </span>","children":null,"spread":false},{"title":"state.py <span style='color:#111;'> 2.47KB </span>","children":null,"spread":false},{"title":"joint_transforms.py <span style='color:#111;'> 37.54KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 171B </span>","children":null,"spread":false},{"title":"sequence_transforms.py <span style='color:#111;'> 6.80KB </span>","children":null,"spread":false},{"title":"optimizer.py <span style='color:#111;'> 1.97KB </span>","children":null,"spread":false}],"spread":true},{"title":"datasets","children":[{"title":"df2dict_dataset.py <span style='color:#111;'> 2.39KB </span>","children":null,"spread":false},{"title":"casia_frame_dataset.py <span style='color:#111;'> 2.25KB </span>","children":null,"spread":false},{"title":"casia_video_dataset.py <span style='color:#111;'> 3.69KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 43B </span>","children":null,"spread":false},{"title":"imagelist_dataset.py <span style='color:#111;'> 948B </span>","children":null,"spread":false},{"title":"dataset_manager.py <span style='color:#111;'> 3.94KB </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"requirements.txt <span style='color:#111;'> 1.48KB </span>","children":null,"spread":false},{"title":"setup.py <span style='color:#111;'> 796B </span>","children":null,"spread":false},{"title":"Makefile <span style='color:#111;'> 144B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 570B </span>","children":null,"spread":false}],"spread":true},{"title":"rgb_track","children":[{"title":"models","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"architectures","children":[{"title":"lite_mobilenet.py <span style='color:#111;'> 3.50KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 525B </span>","children":null,"spread":false},{"title":"transformer.py <span style='color:#111;'> 6.38KB </span>","children":null,"spread":false}],"spread":true},{"title":"wrappers","children":[{"title":"dlas_wrapper.py <span style='color:#111;'> 4.44KB </span>","children":null,"spread":false},{"title":"rgb_simple_wrapper.py <span style='color:#111;'> 1.36KB </span>","children":null,"spread":false},{"title":"rgb_transformer_wrapper.py <span style='color:#111;'> 2.67KB </span>","children":null,"spread":false},{"title":"sdnet_wrapper.py <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false},{"title":"rgb_video_wrapper.py <span style='color:#111;'> 2.05KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"multi_modal_wrapper.py <span style='color:#111;'> 3.02KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"main.py <span style='color:#111;'> 1.36KB </span>","children":null,"spread":false},{"title":"test_config.py <span style='color:#111;'> 2.13KB </span>","children":null,"spread":false},{"title":"rgb_predictor.py <span style='color:#111;'> 1.61KB </span>","children":null,"spread":false},{"title":"rgb_trainer.py <span style='color:#111;'> 2.38KB </span>","children":null,"spread":false},{"title":"compile_submit_file.py <span style='color:#111;'> 723B </span>","children":null,"spread":false},{"title":"configs_final_exp.py <span style='color:#111;'> 7.19KB </span>","children":null,"spread":false}],"spread":true},{"title":"figures","children":[{"title":"pipeline.png <span style='color:#111;'> 157.57KB </span>","children":null,"spread":false}],"spread":true},{"title":"data","children":[{"title":"OpticalFlow.cpp <span style='color:#111;'> 34.26KB </span>","children":null,"spread":false},{"title":"dev_list.txt <span style='color:#111;'> 5.29MB </span>","children":null,"spread":false},{"title":"dev_test_list.txt <span style='color:#111;'> 25.45MB </span>","children":null,"spread":false},{"title":"prepare_lists.py <span style='color:#111;'> 1.33KB </span>","children":null,"spread":false},{"title":"train_list.txt <span style='color:#111;'> 13.37MB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 1.05KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.17KB </span>","children":null,"spread":false},{"title":"multimodal_track","children":[{"title":"multimodal_track","children":[{"title":"configs.py <span style='color:#111;'> 7.99KB </span>","children":null,"spread":false},{"title":"multimodal_predictor.py <span style='color:#111;'> 1.62KB </span>","children":null,"spread":false},{"title":"models","children":[{"title":"wrappers","children":[{"title":"multi_modal_wrapper.py <span style='color:#111;'> 4.03KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"main.py <span style='color:#111;'> 1.38KB </span>","children":null,"spread":false},{"title":"test_config.py <span style='color:#111;'> 2.34KB </span>","children":null,"spread":false},{"title":"multimodal_trainer.py <span style='color:#111;'> 1.59KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明