Subject: Application to download the RGB-D-Face database Name: <your first and last name> Affiliation: <University where you work> Department: <your department> Current position: <your job title> Email: <must be the email at the above mentioned institution> Postal Address: Phone number: I ...
In this paper, we introduce a new dynamic face database, the Sabancı University Dynamic Face (SUDFace) database, which consists of three different speeches articulated with neutral facial expressions. This study aimed to develop a highly controlled dynamic (natural and neutral) face database wi...
离摄像头过近, 人脸超出摄像头范围时, 会有 "OUT OF RANGE" 提醒 / Too close to the camera, or face ROI out of camera area, will have "OUT OF RANGE" warning; 提取特征建立人脸数据库 / Generate face database from images captured 利用摄像头进行人脸识别 / Face recognizer face_reco_from_came...
Oracle Database ORB Intelligence (Independent Publisher) OrbusInfinity Ordnance Survey Places Originality.AI (Independent Publisher) Otto.bot Outlook Tasks [已弃用] Outlook.com Owlbot (Independent Publisher) PagerDuty Pantry (Independent Publisher) Panviva ParishSoft Family Suite Parserr Parseur Partner ...
所有机器学习项目首先需要的都是数据。创建自己的数据集需要时间和多人写作，难度较大。因此，我在网上找了一个看起来比较合适的 RGB-D 人脸数据集（http://www.vap.aau.dk/rgb-d-face-database/），它由一系列人朝着不同方向、带有不同面部表情的 RGB-D 图像构成，非常适合 iPhone X 的应用场景。最终实现...
The following image shows an example of a database named "myfriends". Each group can contain up to 1 million different person objects. Each person object can have up to 248 faces registered.After you create and train a group, you can do identification against the group with a new detected...
├── FaceDatabase # 这是存放照片的文件夹,想要识别谁就把她的照片放这里 ├── main.py ├── model #存放模型文件,你直接把你训练好的模型(推理模型)丢里面就行 └── utils.py Paddle-Lite 部署 Paddle Lite是一个高性能、轻量级、灵活性强且易于扩展的深度学习推理框架,定位支持包括移动端、嵌入式...
王铁震：以大模型为例，大家最熟悉的 ChatGPT 其实就是一个闭源的模型，目前 GPT-4 是效果最好的模型，这毋庸置疑。很多企业在创业的早期也都是选择接入 ChatGPT，直接在外面做一些 prompt engineering，做 fact database，就可以很快地把产品做成。但是随着规模的扩大，或者说因为不同领域的一些要求，就会发现数据...
The following image shows an example of a database named"myfriends". Each group can contain up to 1 million different person objects. Each person object can have up to 248 faces registered. After you create and train a group, you can do identification against the group with a new detected...