1 code implementation • 30 Aug 2017 • Jiahao Pang, Wenxiu Sun, Jimmy SJ. Ren, Chengxi Yang, Qiong Yan
As opposed to directly learning the disparity at the second stage, we show that residual learning provides more effective refinement.
1 code implementation • NeurIPS 2015 • Jimmy SJ. Ren, Li Xu, Qiong Yan, Wenxiu Sun
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.
no code implementations • 29 Jan 2015 • Jimmy SJ. Ren, Li Xu
We recently have witnessed many ground-breaking results in machine learning and computer vision, generated by using deep convolutional neural networks (CNN).
no code implementations • NeurIPS 2014 • Li Xu, Jimmy SJ. Ren, Ce Liu, Jiaya Jia
Many fundamental image-related problems involve deconvolution operators.
Ranked #1 on Image Compression on FER2013
no code implementations • 29 Oct 2013 • Jimmy SJ. Ren, Wei Wang, Jiawei Wang, Stephen Liao
Sophisticated automatic incident detection (AID) technology plays a key role in contemporary transportation systems.
no code implementations • 3 Aug 2013 • Jimmy SJ. Ren, Wei Wang, Jiawei Wang, Stephen Shaoyi Liao
We argue that if the bias-variance trade-off is to be better balanced by a more effective feature selection method unlabeled data is very likely to boost the classification performance.