ID 原文 译文
25945 针对点云空间三维信息非结构化和旋转易变性对预测结果的影响，提出一种带特征监控的三维信息编解码卷积神经网络，该网络可实现三维空间下单目深度图的端对端无标记人体姿态估计。 Aiming at the impact of unstructured and rotational variability of three-dimensional information in point cloud on prediction results, a feature-supervised three-dimensional information encoding and decoding convolution deep learning network is proposed.
25946 所设计的网络由特征监控编解码组件串联而成，该组件第一部分使用三维卷积模块以类似沙漏结构的形式组合设计，实现对特征图的编码和解码。 The network is composed of feature monitoring coding and decoding modules in series. In the first part of the module, a three-dimensional convolution module is used in the form of hour glass structure to realize the coding and decoding ofthe feature map.
25947 第二部分以不同参数残差块并联，实现对特征图的监控融合，第一部分与第二部分首尾连接构成组件。 In the second part, the residual blocks of different parameters are connected in parallel to realize the monitoring and fusion of feature maps．
25948 特征监控编解码组件能根据数据集大小，通过串联的方式搭建不同深度的网络，同时根据数据分辨率，设置组件参数，实现由粗到精的特征学习，最终获得最佳网络。 Feature monitored coding and decoding modules can build networks with different depths in series according to the size of data sets. At the same time, according to the data resolution, modules parameters can be set to realize feature learning from rough to fine，and ultimately obtain the best network．
25949 通过 ITOP 数据库的实验表明，该网络实现了空间三维信息的端到端深度学习，显著提高了系统性能并具有更高的精度。 The experiment of ITOP database shows that the network achieves the end-to-end deep learning of three-dimensional information, significantly improves the system performance and has higher precision accuracy．
25950 为防止签名验证者利用部分签名取得不公平的优势，Huang 等人提出混淆乐观公平交换(AmbiguousOptimistic Fair Exchange，AOFE)方案及其一般构造方法，但是其构造方法没有考虑真实的用户环境。 A generic ambiguous optimistic fair exchange (AOFE) scheme, a variant of OFE, is proposed by Huang et al. The AOFE scheme prevents signature verifiers from convincing anybody about the authorship of a partial signature generated by the signer. However, the AOFE scheme cannot be directly applied to an actual user environment．
25951 在基于 IBC(Iden-tity-Based Cryptography)的用户环境下，文章提出基于身份的混淆乐观公平交换(ID-AOFE)方案构造方法、方案实例、及其选择身份安全模型。 A generic AOFE scheme and an instantiation of the generic construction in an identity-based user environment were proposed in this paper.
25952 提出的 ID-AOFE 构造方法对 Huang 等人的 AOFE 方案进行了简化，采用具有信息提取功能的证据不可区分证明算法替换原方案模型中的基于标签加解密和零知识证明算法。 In the generic construction of identity-based AOFE (ID-AOFE), the tag-based encryption and zero-knowledge proof algorithms in Huang et al. AOFE was removed and the non-interactive witness indistinguishable proof algorithms extracting the hided witness via keyswas employed.
25953 ID-AOFE 安全模型以 Huang 等人的 AOFE 安全模型为基础，融合了选择身份安全模型，并对 ID-AOFE 方案的安全性进行了归纳和重新定义。 Furthermore, we summarized and redefined the security of the ID-AOFE scheme. Then, an ID-AOFE security model was defined based on the Huang et al. AOFE security model and the selective identity security model．
25954 在选择身份安全模型下，提出的 ID-AOFE 方案实例的公平性被规约到经典密码原语的安全性。 Under the selective identity security model of ID-AOFE, the fairness of our scheme is reduced to the securities of several classical cryptographic primitives．