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20052023
most citedDeepID3: Face Recognition with Very Deep Neural Networks

895 citations · 2k across the 44 of their papers we have counts for

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Showing 2017 · cs.CVShow all

27 papers · 2 filters

cs.CV2017

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…

cs.CV2017

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…

cs.CV2017★ 112 cited

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…

cs.CV2017

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…

cs.CV2017★ 90 cited

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…

cs.CV2017

Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection

Hongyang Li, Yu Liu, Wanli Ouyang +1

In this paper, we propose a zoom-out-and-in network for generating object proposals. A key observation is that it is difficult to classify anchors of different sizes with the same…