J. Ren

Publications
Influence

Cascade Residual Learning: A Two-Stage Convolutional Neural Network for Stereo Matching

Jiahao Pang, Wenxiu Sun, J. Ren, Chengxi Yang, Q. Yan
Computer Science
IEEE International Conference on Computer Vision…
30 August 2017

Leveraging on the recent developments in convolutional neural networks (CNNs), matching dense correspondence from a stereo pair has been cast as a learning problem, with performance exceeding traditional approaches. Expand

Deep Convolutional Neural Network for Image Deconvolution

L. Xu, J. Ren, Ce Liu, J. Jia
Computer Science, Mathematics
NIPS
8 December 2014

We use the convolutional neural network (CNN) to learn the deconvolution operation without the need to know the cause of visual artifacts. Expand

Deep Edge-Aware Filters

L. Xu, J. Ren, Q. Yan, Renjie Liao, J. Jia
Computer Science
ICML
6 July 2015

A deep convolutional neural network with a gradient domain training procedure gives rise to a powerful tool to approximate various filters without knowing the original models and implementation details. Expand

3D Human Pose Estimation in the Wild by Adversarial Learning

Wei Yang, Wanli Ouyang, X. Wang, J. Ren, Hongsheng Li, Xiaogang Wang
Computer Science
IEEE/CVF Conference on Computer Vision and…
26 March 2018

In this paper, we propose an adversarial learning framework, which distills the 3D human pose structures learned from the fully annotated constrained 3D pose dataset to in-the-wild images with only 2D pose annotations. Expand

Shepard Convolutional Neural Networks

J. Ren, L. Xu, Q. Yan, Wenxiu Sun
Computer Science
NIPS
7 December 2015

In this paper, we draw on Shepard interpolation and design Shepard Convolutional Neural Networks (ShCNN) which efficiently realizes end-to-end trainable TVI operators in the network. Expand

Look, Listen and Learn - A Multimodal LSTM for Speaker Identification

J. Ren, Yongtao Hu, +4 authors Q. Yan
Computer Science
AAAI
12 February 2016

We propose a multimodal LSTM architecture which seamlessly unifies both visual and auditory modalities from the beginning of each sequence input. Expand

Learning Dual Convolutional Neural Networks for Low-Level Vision

J. Pan, Sifei Liu, +8 authors Ming-Hsuan Yang
Computer Science
IEEE/CVF Conference on Computer Vision and…
14 May 2018

We propose a general dual convolutional neural network (DualCNN) for low-level vision problems, e.g., super-resolution, edge-preserving filtering, deraining and dehazing. Expand

LSTM Pose Machines

Yue Luo, J. Ren, +5 authors L. Lin
Computer Science
IEEE/CVF Conference on Computer Vision and…
18 December 2017

We showed that if we were to impose the weight sharing scheme to the multi-stage CNN, it could be re-written as a Recurrent Neural Network (RNN). Expand

Deep Multimodal Speaker Naming

Yongtao Hu, J. Ren, Jingwen Dai, C. Yuan, L. Xu, W. Wang
Computer Science
ACM Multimedia
17 July 2015

We propose a novel convolutional neural networks (CNN) based learning framework to tackle the task of speaker naming. Expand

Deep Reasoning with Knowledge Graph for Social Relationship Understanding

Zhouxia Wang, Tianshui Chen, J. Ren, Weihao Yu, H. Cheng, L. Lin
Computer Science
IJCAI
1 July 2018

We propose an end-to-end trainable Graph Reasoning Model (GRM), in which a propagation mechanism is learned to propagate node message through the graph to explore the interaction between persons of interest and the contextual objects. Expand

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