128 citations · 724 across the 72 of their papers we have counts for
9 papers · 1 filter
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…
Gated Channel Transformation for Visual Recognition
Zongxin Yang, Linchao Zhu, Yu Wu +1
In this work, we propose a generally applicable transformation unit for visual recognition with deep convolutional neural networks. This transformation explicitly models channel re…
Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning
Linchao Zhu, Sercan O. Arik, Yi Yang +1
We propose a novel adaptive transfer learning framework, learning to transfer learn (L2TL), to improve performance on a target dataset by careful extraction of the related informat…
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…
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…
Cubic LSTMs for Video Prediction
Hehe Fan, Linchao Zhu, Yi Yang
Predicting future frames in videos has become a promising direction of research for both computer vision and robot learning communities. The core of this problem involves moving ob…
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…
Filter Pruning by Switching to Neighboring CNNs with Good Attributes
Yang He, Ping Liu, Linchao Zhu +1
Filter pruning is effective to reduce the computational costs of neural networks. Existing methods show that updating the previous pruned filter would enable large model capacity a…
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
Ruijie Quan, Xuanyi Dong, Yu Wu +2
Prevailing deep convolutional neural networks (CNNs) for person re-IDentification (reID) are usually built upon ResNet or VGG backbones, which were originally designed for classifi…