63 citations · 138 across the 5 of their papers we have counts for
5 papers
ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network
Zhangheng Li, Jia-Xing Zhong, Jingjia Huang +3
In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previ…
Deep AutoEncoder-based Lossy Geometry Compression for Point Clouds
Wei Yan, Yiting shao, Shan Liu +3
Point cloud is a fundamental 3D representation which is widely used in real world applications such as autonomous driving. As a newly-developed media format which is characterized…
Compressing Neural Language Models by Sparse Word Representations
Yunchuan Chen, Lili Mou, Yan Xu +2
Neural networks are among the state-of-the-art techniques for language modeling. Existing neural language models typically map discrete words to distributed, dense vector represent…
Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking
Nannan Li, Dan Xu, Zhenqiang Ying +2
In this paper, we address the problem of searching action proposals in unconstrained video clips. Our approach starts from actionness estimation on frame-level bounding boxes, and…
Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation
Lili Mou, Yiping Song, Rui Yan +3
Using neural networks to generate replies in human-computer dialogue systems is attracting increasing attention over the past few years. However, the performance is not satisfactor…