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Co-attending Free-form Regions and Detections with Multi-modal Multiplicative Feature Embedding for Visual Question Answering
Pan Lu, Hongsheng Li, Wei Zhang +2
Recently, the Visual Question Answering (VQA) task has gained increasing attention in artificial intelligence. Existing VQA methods mainly adopt the visual attention mechanism to a…
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
Xingang Pan, Xiaohang Zhan, Jianping Shi +3
Convolutional neural networks (CNNs) are usually built by stacking convolutional operations layer-by-layer. Although CNN has shown strong capability to extract semantics from raw p…
Rethinking Feature Discrimination and Polymerization for Large-scale Recognition
Yu Liu, Hongyang Li, Xiaogang Wang
Feature matters. How to train a deep network to acquire discriminative features across categories and polymerized features within classes has always been at the core of many comput…
Spontaneous Symmetry Breaking in Neural Networks
Ricky Fok, Aijun An, Xiaogang Wang
We propose a framework to understand the unprecedented performance and robustness of deep neural networks using field theory. Correlations between the weights within the same layer…
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang, Tao Xu, Hongsheng Li +4
Although Generative Adversarial Networks (GANs) have shown remarkable success in various tasks, they still face challenges in generating high quality images. In this paper, we prop…
HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis
Xihui Liu, Haiyu Zhao, Maoqing Tian +5
Pedestrian analysis plays a vital role in intelligent video surveillance and is a key component for security-centric computer vision systems. Despite that the convolutional neural…