Search Results for author: Shuang Wu

Found 13 papers, 4 papers with code

MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition

no code implementations ACL 2021 Shuang Wu, Xiaoning Song, ZhenHua Feng

This paper presents a novel Multi-metadata Embedding based Cross-Transformer (MECT) to improve the performance of Chinese NER by fusing the structural information of Chinese characters.

Chinese Named Entity Recognition NER

Aggregated Multi-GANs for Controlled 3D Human Motion Prediction

no code implementations17 Mar 2021 Zhenguang Liu, Kedi Lyu, Shuang Wu, Haipeng Chen, Yanbin Hao, Shouling Ji

Our method is compelling in that it enables manipulable motion prediction across activity types and allows customization of the human movement in a variety of fine-grained ways.

Human motion prediction motion prediction

Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers

2 code implementations5 Sep 2019 Yukuan Yang, Shuang Wu, Lei Deng, Tianyi Yan, Yuan Xie, Guoqi Li

In this way, all the operations in the training and inference can be bit-wise operations, pushing towards faster processing speed, decreased memory cost, and higher energy efficiency.

Quantization

Convolution with even-sized kernels and symmetric padding

1 code implementation NeurIPS 2019 Shuang Wu, Guanrui Wang, Pei Tang, Feng Chen, Luping Shi

Compact convolutional neural networks gain efficiency mainly through depthwise convolutions, expanded channels and complex topologies, which contrarily aggravate the training process.

Continual Learning Image Classification

Robust and Efficient Graph Correspondence Transfer for Person Re-identification

no code implementations15 May 2018 Qin Zhou, Heng Fan, Hua Yang, Hang Su, Shibao Zheng, Shuang Wu, Haibin Ling

To address this problem, in this paper, we present a robust and efficient graph correspondence transfer (REGCT) approach for explicit spatial alignment in Re-ID.

Graph Matching Person Re-Identification

L1-Norm Batch Normalization for Efficient Training of Deep Neural Networks

no code implementations27 Feb 2018 Shuang Wu, Guoqi Li, Lei Deng, Liu Liu, Yuan Xie, Luping Shi

Batch Normalization (BN) has been proven to be quite effective at accelerating and improving the training of deep neural networks (DNNs).

Quantization

Training and Inference with Integers in Deep Neural Networks

2 code implementations ICLR 2018 Shuang Wu, Guoqi Li, Feng Chen, Luping Shi

Researches on deep neural networks with discrete parameters and their deployment in embedded systems have been active and promising topics.

Continual Learning

Slim Embedding Layers for Recurrent Neural Language Models

no code implementations27 Nov 2017 Zhongliang Li, Raymond Kulhanek, Shaojun Wang, Yunxin Zhao, Shuang Wu

When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of recurrent neural language models.

Language Modelling

Zero-shot Event Detection using Multi-modal Fusion of Weakly Supervised Concepts

no code implementations CVPR 2014 Shuang Wu, Sravanthi Bondugula, Florian Luisier, Xiaodan Zhuang, Pradeep Natarajan

Current state-of-the-art systems for visual content analysis require large training sets for each class of interest, and performance degrades rapidly with fewer examples.

Event Detection

A unified model of short-range and long-range motion perception

no code implementations NeurIPS 2010 Shuang Wu, Xuming He, Hongjing Lu, Alan L. Yuille

The human vision system is able to effortlessly perceive both short-range and long-range motion patterns in complex dynamic scenes.

Model selection and velocity estimation using novel priors for motion patterns

no code implementations NeurIPS 2008 Shuang Wu, Hongjing Lu, Alan L. Yuille

Psychophysical experiments show that humans are better at perceiving rotation and expansion than translation.

Model Selection

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