To this end, we propose a novel deep multi-view ensemble model. The structure of each layer is composed of an ensemble of encoders or decoders and mask operations. The multi-view ensemble of encoders or decoders enable the network to benefit from local complementary information and preserve ...
R. Martin-Brualla, N. Snavely, T. Funkhouser. IBRNet: Learning multi-view image-based rendering. InProceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, Nashville, USA pp. 4688–4697, 2021. DOI:https://doi.org/10.1109/CVPR46437.2021.00466 ...
Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision NIPS 2016 Torch 7 Deep disentangled representations for volumetric reconstruction ECCV 2016 Multi-view 3D Models from Single Images with a Convolutional Network ECCV 2016 Tensorflow Single Image 3D Interpreter...
LAMDA-SSL: a comprehensive semi-supervised learning toolkit Jia, Lin-Han; Guo, Lan-Zhe; Zhou, Zhi; Li, Yu-Feng Sci China Inf Sci, 2024, 67(1): 117101Keywords: semi-supervised learning; toolkit; Python; statistical learning; deep learningCite...
Multiview CNNs:[23, 18]尝试将3D点云或形状渲染为2D图像,然后应用2D卷积网络对它们进行分类。通过精心设计的图像CNN,这一系列方法已经在形状分类和检索任务上取得了主导性能[21]。然而,将它们扩展到场景理解或其他3D任务(如点分类和形状补全)是很重要的。Spectral CNNs:一些最新的工作[4,16]在网格上使用谱CNN...
Furthermore, the authors also devised a Hierarchical Deep Word Embedding model by integrating sparse constraints and an improved RELU operator to address click feature prediction from visual features37. In particular, the integration of different types of features is difficult for multiview data, thus...
[arXiv 2022] Self-supervised Graph Representation Learning for Black Market Account Detection [paper] [arXiv 2022] Contrastive Deep Graph Clustering with Learnable Augmentation [paper] [arXiv 2022] Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View [paper] [arXiv...
With the continuous advancement of deep learning methods, more and more high-performance 3D human pose estimation methods based on deep learning have been proposed. However, due to the human occlusion of the picture and the large demand for training scale, there are still challenges in 3D human...
and knees. These methods are categorized based on their use of monocular or multi-view images and videos, and further classified by the deep learning algorithms they employ, such as CNNs, GCNs, Transformers, and hybrid models. The general procedure for single-person 3D-HPE is summarized in Fi...
International Conference on Health, Science and Technology Articles / News / Press releases The Non-Uniform Distribution of User’s Calls in Time & Space: heterogeneous wireless networks Synthetic-aperture Radar Image Processing A Technology conference is a great way to expand your knowledge ...