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20152023
most citedLearning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

517 citations · 1.7k across the 49 of their papers we have counts for

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Showing 2018 · cs.CVShow all

7 papers · 2 filters

cs.CV2018★ 23 cited

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration

Yang He, Ping Liu, Ziwei Wang +2

Previous works utilized ''smaller-norm-less-important'' criterion to prune filters with smaller norm values in a convolutional neural network. In this paper, we analyze this norm-b…

cs.CV2018★ 2 cited

Learning Discriminators as Energy Networks in Adversarial Learning

Pingbo Pan, Yan Yan, Tianbao Yang +1

We propose a novel framework for structured prediction via adversarial learning. Existing adversarial learning methods involve two separate networks, i.e., the structured predictio…

cs.CV2018★ 68 cited

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Yang He, Guoliang Kang, Xuanyi Dong +2

This paper proposed a Soft Filter Pruning (SFP) method to accelerate the inference procedure of deep Convolutional Neural Networks (CNNs). Specifically, the proposed SFP enables th…

cs.CV2018★ 7 cited

Asymptotic Soft Filter Pruning for Deep Convolutional Neural Networks

Yang He, Xuanyi Dong, Guoliang Kang +3

Deeper and wider Convolutional Neural Networks (CNNs) achieve superior performance but bring expensive computation cost. Accelerating such over-parameterized neural network has rec…

cs.CV2018★ 30 cited

Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

Xuanyi Dong, Shoou-I Yu, Xinshuo Weng +3

In this paper, we present supervision-by-registration, an unsupervised approach to improve the precision of facial landmark detectors on both images and video. Our key observation…

cs.CV2018★ 54 cited

Style Aggregated Network for Facial Landmark Detection

Xuanyi Dong, Yan Yan, Wanli Ouyang +1

Recent advances in facial landmark detection achieve success by learning discriminative features from rich deformation of face shapes and poses. Besides the variance of faces thems…