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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 2019 · cs.CVShow all

8 papers · 2 filters

cs.CV2019

Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement

Aming Wu, Yahong Han, Linchao Zhu +1

Most state-of-the-art methods of object detection suffer from poor generalization ability when the training and test data are from different domains, e.g., with different styles. T…

cs.CV2019★ 19 cited

Baidu-UTS Submission to the EPIC-Kitchens Action Recognition Challenge 2019

Xiaohan Wang, Yu Wu, Linchao Zhu +1

In this report, we present the Baidu-UTS submission to the EPIC-Kitchens Action Recognition Challenge in CVPR 2019. This is the winning solution to this challenge. In this task, th…

cs.CV2019★ 9 cited

FASTER Recurrent Networks for Efficient Video Classification

Linchao Zhu, Laura Sevilla-Lara, Du Tran +3

Typical video classification methods often divide a video into short clips, do inference on each clip independently, then aggregate the clip-level predictions to generate the video…

cs.CV2019★ 48 cited

Query-efficient Meta Attack to Deep Neural Networks

Jiawei Du, Hu Zhang, Joey Tianyi Zhou +2

Black-box attack methods aim to infer suitable attack patterns to targeted DNN models by only using output feedback of the models and the corresponding input queries. However, due…

cs.CV2019★ 137 cited

Network Pruning via Transformable Architecture Search

Xuanyi Dong, Yi Yang

Network pruning reduces the computation costs of an over-parameterized network without performance damage. Prevailing pruning algorithms pre-define the width and depth of the prune…

cs.CV2019★ 7 cited

Sim-Real Joint Reinforcement Transfer for 3D Indoor Navigation

Fengda Zhu, Linchao Zhu, Yi Yang

There has been an increasing interest in 3D indoor navigation, where a robot in an environment moves to a target according to an instruction. To deploy a robot for navigation in th…