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A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection
Zhe Chen, Wanli Ouyang, Tongliang Liu +1
Deep learning-based computer vision is usually data-hungry. Many researchers attempt to augment datasets with synthesized data to improve model robustness. However, the augmentatio…
Transform-Invariant Convolutional Neural Networks for Image Classification and Search
Xu Shen, Xinmei Tian, Anfeng He +2
Convolutional neural networks (CNNs) have achieved state-of-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invaria…
Patch Reordering: a Novel Way to Achieve Rotation and Translation Invariance in Convolutional Neural Networks
Xu Shen, Xinmei Tian, Shaoyan Sun +1
Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance on many visual recognition tasks. However, the combination of convolution and pooling operations…
Continuous Dropout
Xu Shen, Xinmei Tian, Tongliang Liu +2
Dropout has been proven to be an effective algorithm for training robust deep networks because of its ability to prevent overfitting by avoiding the co-adaptation of feature detect…
An End-to-end Framework for Unconstrained Monocular 3D Hand Pose Estimation
Sanjeev Sharma, Shaoli Huang, Dacheng Tao
This work addresses the challenging problem of unconstrained 3D hand pose estimation using monocular RGB images. Most of the existing approaches assume some prior knowledge of hand…
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Haoyu He, Jing Zhang, Qiming Zhang +1
Human parsing, or human body part semantic segmentation, has been an active research topic due to its wide potential applications. In this paper, we propose a novel GRAph PYramid M…