9 citations · 32 across the 11 of their papers we have counts for
11 papers
Simple and Scalable Nearest Neighbor Machine Translation
Yuhan Dai, Zhirui Zhang, Qiuzhi Liu +4
NN-MT is a straightforward yet powerful approach for fast domain adaptation, which directly plugs pre-trained neural machine translation (NMT) models with domain-specific token-…
Anti-aliasing Predictive Coding Network for Future Video Frame Prediction
Chaofan Ling, Weihua Li, Junpei Zhong
We introduce here a predictive coding based model that aims to generate accurate and sharp future frames. Inspired by the predictive coding hypothesis and related works, the total…
Predictive Coding Based Multiscale Network with Encoder-Decoder LSTM for Video Prediction
Chaofan Ling, Junpei Zhong, Weihua Li
We present a multi-scale predictive coding model for future video frames prediction. Drawing inspiration on the ``Predictive Coding" theories in cognitive science, it is updated by…
Pyramidal Predictive Network: A Model for Visual-frame Prediction Based on Predictive Coding Theory
Chaofan Ling, Junpei Zhong, Weihua Li
Visual-frame prediction is a pixel-dense prediction task that infers future frames from past frames. Lacking of appearance details, low prediction accuracy and high computational o…
Universal Representations: A Unified Look at Multiple Task and Domain Learning
Wei-Hong Li, Xialei Liu, Hakan Bilen
We propose a unified look at jointly learning multiple vision tasks and visual domains through universal representations, a single deep neural network. Learning multiple problems s…
The 4th International Workshop on Smart Simulation and Modelling for Complex Systems
Xing Su, Yan Kong, Weihua Li
Computer-based modelling and simulation have become useful tools to facilitate humans to understand systems in different domains, such as physics, astrophysics, chemistry, biology,…
Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People Detection
Fa-Ting Hong, Wei-Hong Li, Wei-Shi Zheng
Important people detection is to automatically detect the individuals who play the most important roles in a social event image, which requires the designed model to understand a h…
Learning to Impute: A General Framework for Semi-supervised Learning
Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen
Recent semi-supervised learning methods have shown to achieve comparable results to their supervised counterparts while using only a small portion of labels in image classification…
Learning to Learn Relation for Important People Detection in Still Images
Wei-Hong Li, Fa-Ting Hong, Wei-Shi Zheng
Humans can easily recognize the importance of people in social event images, and they always focus on the most important individuals. However, learning to learn the relation betwee…
One-pass Person Re-identification by Sketch Online Discriminant Analysis
Wei-Hong Li, Zhuowei Zhong, Wei-Shi Zheng
Person re-identification (re-id) is to match people across disjoint camera views in a multi-camera system, and re-id has been an important technology applied in smart city in recen…
PersonRank: Detecting Important People in Images
Wei-Hong Li, Benchao Li, Wei-Shi Zheng
Always, some individuals in images are more important/attractive than others in some events such as presentation, basketball game or speech. However, it is challenging to find impo…