今天主要会讲解人脸检测的13种欺骗攻击中的ZSFA(Zero-Shot Face Anti-spoofing)问题,包括打印、重放、3D掩码等,利用新的深度树网络(DTN),以无监督的方式将欺骗样本划分为语义子组。当数据样本到达、已知或未知攻击时,DTN将其划分到最相似的欺骗集群,并做出二进制决策。最后实验表明,达到了ZSFA多个测试协议的最新水平...
能力强且通用:RAM可识别任意常见类别,支持中英文,精度上其Zero-Shot能力超越了有监督模型,高于CLIP/BLIP等经典多模态模型20+点,并可对标甚至超越Google的商用API; 可复现且成本低:RAM完全基于开源数据训练,通过自动化的数据引擎获取了上亿级无须人工标注的高质量图像标签,RAM的基础版本模型只需八卡训练1天,最强版本...
Zero-Shot Facial Expression Recognition with Multi-label Label PropagationFacial expression recognition classifies a face image into one of several discrete emotional categories. We have a lot of exclusive or non-exclusive emotional classes to describe the varied and......
一、RAM的优势 能力强且通用:RAM可识别任意常见类别,支持中英文,精度上其Zero-Shot能力超越了有监督模型,高于CLIP/BLIP等经典多模态模型20+点,并可对标甚至超越Google的商用API; 可复现且成本低:RAM完全基于开源数据训练,通过自动化的数据引擎获取 了上亿级无须人工标注的高质量图像标签,RAM的基础版本模型只需八卡...
face”.Inthispaper,wefocusontheproblemofzero-shotlearning wherevisualclassifiersarelearnedfromsemanticembeddingsand relationshipstoothercategories. paradigmsoftransferringknowledge.Thefirstparadigm istouseimplicitknowledgerepresentations,i.e.semantic embeddings.Inthisapproach,onelearnsavectorrepresen- ...
Contrastive loss and triplet loss functions are now used for high-quality face embeddings, which have become the foundation for modern facial recognition. Few-shot Learning Few-shot learning, also known as low-shot learning, uses a small set of examples from new data to learn a new task. ...
2. Zero-shot 解决VQA问题之前关于CLIP的一些研究就尝试过用CLIP解决VQA问题,但是效果很差。作者认为效果差不是CLIP的问题,而是之前的人都没用好,没有完全发挥出CLIP的潜力。为了通过zero-shot learning解决VQA任务,一个核心的问题是如何将VQA任务利用prompt的思路转化成完形填空任务。只有将VQA任务转换成更接近CLIP...
Zero-shot learning, the task of learning to recognize new classes not seen during training, has received considerable attention in the case of 2D image cla
This motivates us to propose a novel zero-shot approach, allowing machines to identify characters and predict speaker names based solely on unannotated comic images. In spite of their importance in real-world applications, these task have largely remained unexplored due to challenges in story ...
OntheEffectivenessofVision TransformersforZero-shotFace Anti-Spoofing 提出了利用Vision Transformer 预训练模型进行迁移学习,针对zero-shot人脸活体检测任务。 说是迁移学习,实际只是做微调 。 说是zero-shot,但是模型方面并没有针对该任务做任何调整,是在评估时用zero-shot ...