62 citations · 243 across the 8 of their papers we have counts for
8 papers
Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning
Yukai Shi, Keze Wang, Chongyu Chen +2
Single image super resolution (SR), which refers to reconstruct a higher-resolution (HR) image from the observed low-resolution (LR) image, has received substantial attention due t…
Accurate Single Stage Detector Using Recurrent Rolling Convolution
Jimmy Ren, Xiaohao Chen, Jianbo Liu +5
Most of the recent successful methods in accurate object detection and localization used some variants of R-CNN style two stage Convolutional Neural Networks (CNN) where plausible…
Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning
Yukai Shi, Keze Wang, Li Xu +1
Recently, machine learning based single image super resolution (SR) approaches focus on jointly learning representations for high-resolution (HR) and low-resolution (LR) image patc…
Look, Listen and Learn - A Multimodal LSTM for Speaker Identification
Jimmy Ren, Yongtao Hu, Yu-Wing Tai +4
Speaker identification refers to the task of localizing the face of a person who has the same identity as the ongoing voice in a video. This task not only requires collective perce…
Deep Multimodal Speaker Naming
Yongtao Hu, Jimmy Ren, Jingwen Dai +3
Automatic speaker naming is the problem of localizing as well as identifying each speaking character in a TV/movie/live show video. This is a challenging problem mainly attributes…
On Vectorization of Deep Convolutional Neural Networks for Vision Tasks
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). While the success main…