recognition efficiency and intelligence level of traditional CAPP systems and effectively recognize the machining features, this paper proposes a novel machining feature recognition method for mechanical parts based on Mesh-Faster RCNN, which combines the original MeshCNN model with the Faster RCNN model...
论文采用了3D convnet来实现了end-to-end的训练,提出快速的Region Convolutional 3D Network (R-C3D),用于连续视频流的行为检测。R-C3D使用3D卷积提取视频特征,采用了Faster-RCNN形式的思路,即先生成proposal,再roi-pooling,最后进行分类和边界回归。 R-C3D发表在CVPR2017,并在ActivityNet Large Scale Activity Rec...
[43] Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. NIPS, 2015. 2, 3, 5 [44] Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li. Pv-rcnn: Pointvoxel ...
it can induce the triangles normals to be inverted. The triangles angle values may also be different if they are oriented but I did not check. And since these features are computed inside the model and fed to the GCNN encoder, I would say we are not forwarding the right mesh to the ...
for object sequences filmed with an RGB-D camera. This project can prepare training and testing data for various deep learning projects such as 6D object pose estimation projects singleshotpose, and many object detection (e.g., faster rcnn) and instance segmentation (e.g., mask rcnn) proje...
The ex- perimental results show that SA-HMR is not only effective in recovering absolute positions and meshes that are in ac- cordance with the given scene, but also significantly faster than the optimization-based baselines. In summary, we make the following contributions: • The first ...
(1) (2) The sum of objectives is optimized over the entire sequence of length T : T T −1 E= (Eptroj + Eptrior) + (Estm joint + Estm param), (3) t=1 t=1 returning model parameters Θt for every frame t of the se- quence. For faster convergence to a more accurate ...
In order to facilitate processing, for different numbers of target detection candidate regions obtained by using Faster-RCNN in different pictures, we uni- formly use zero vectors padding to fill the candidate regions to the maximum scale K. Ultimately, the image feature we get is a feature ...
(2018), we use CNN to train deep models for all sections, which is much faster than Bi-GRU in terms of training speed. Compared to Bi-GRU, CNN can naturally encode the k-gram features for a document/documents. In addition, by incorporating with attention mechanism, the network can choose...
Wen developed 2 algorithms for obtaining a cut graph. The first is the implementation of the algorithm in the book31, and the other is the translation of David Gu’s C++ code30, which is much faster than version 1. We conducted experiments on Fertility. As shown in Fig.4a, there are ...