147 citations · 182 across the 2 of their papers we have counts for
8 papers
AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
Zhongyue Zhang, Guangyin Jin, Yuxuan Liang +2
Modeling spatial dependencies is central to spatiotemporal data analysis using Graph Neural Networks (GNNs). Traditional methods rely on distance-based kernels with predefined para…
Improving Semantic Segmentation via Self-Training
Yi Zhu, Zhongyue Zhang, Chongruo Wu +6
Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…
ResNeSt: Split-Attention Networks
Hang Zhang, Chongruo Wu, Zhongyue Zhang +9
It is well known that featuremap attention and multi-path representation are important for visual recognition. In this paper, we present a modularized architecture, which applies t…
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
Jian Guo, He He, Tong He +13
We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and natural language processing based on Apache MXNet (incubating). These toolkits provide state-of-…
Bag of Freebies for Training Object Detection Neural Networks
Zhi Zhang, Tong He, Hang Zhang +3
Training heuristics greatly improve various image classification model accuracies~\cite{he2018bag}. Object detection models, however, have more complex neural network structures an…
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He, Zhi Zhang, Hang Zhang +3
Much of the recent progress made in image classification research can be credited to training procedure refinements, such as changes in data augmentations and optimization methods.…