90 citations · 156 across the 6 of their papers we have counts for
6 papers
MG-SAGC: A multiscale graph and its self-adaptive graph convolution network for 3D point clouds
Bo Wu, Bo Lang
To enhance the ability of neural networks to extract local point cloud features and improve their quality, in this paper, we propose a multiscale graph generation method and a self…
Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search
Xianglong Liu, Lei Huang, Cheng Deng +2
Hash based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming…
Decorrelated Batch Normalization
Lei Huang, Dawei Yang, Bo Lang +1
Batch Normalization (BN) is capable of accelerating the training of deep models by centering and scaling activations within mini-batches. In this work, we propose Decorrelated Batc…
DGCNN: Disordered Graph Convolutional Neural Network Based on the Gaussian Mixture Model
Bo Wu, Yang Liu, Bo Lang +1
Convolutional neural networks (CNNs) can be applied to graph similarity matching, in which case they are called graph CNNs. Graph CNNs are attracting increasing attention due to th…
Projection Based Weight Normalization for Deep Neural Networks
Lei Huang, Xianglong Liu, Bo Lang +1
Optimizing deep neural networks (DNNs) often suffers from the ill-conditioned problem. We observe that the scaling-based weight space symmetry property in rectified nonlinear netwo…
Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks
Lei Huang, Xianglong Liu, Bo Lang +3
Orthogonal matrix has shown advantages in training Recurrent Neural Networks (RNNs), but such matrix is limited to be square for the hidden-to-hidden transformation in RNNs. In thi…