Search Results for author: Haifeng Sun

Found 9 papers, 2 papers with code

AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation

1 code implementation19 Jul 2020 Weiting Huang, Pengfei Ren, Jingyu Wang, Qi Qi, Haifeng Sun

In this paper, we propose an adaptive weighting regression (AWR) method to leverage the advantages of both detection-based and regression-based methods.

3D Hand Pose Estimation

Adversarial and Domain-Aware BERT for Cross-Domain Sentiment Analysis

no code implementations ACL 2020 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao

To tackle these problems, we design a post-training procedure, which contains the target domain masked language model task and a novel domain-distinguish pre-training task.

Language Modelling Sentiment Analysis +1

Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification

no code implementations IJCNLP 2019 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao, Chun Wang, Bing Ma

It has been demonstrated that multiple senses of a word actually reside in linear superposition within the word embedding so that specific senses can be extracted from the original word embedding.

General Classification Text Classification

Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification

no code implementations IJCNLP 2019 Chunning Du, Haifeng Sun, Jingyu Wang, Qi Qi, Jianxin Liao, Tong Xu, Ming Liu

Aspect-level sentiment classification is a crucial task for sentiment analysis, which aims to identify the sentiment polarities of specific targets in their context.

General Classification Sentiment Analysis

OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks

1 code implementation CVPR 2019 Jiashi Li, Qi Qi, Jingyu Wang, Ce Ge, Yujian Li, Zhangzhang Yue, Haifeng Sun

Many channel pruning works utilize structured sparsity regularization to zero out all the weights in some channels and automatically obtain structure-sparse network in training stage.

Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation

no code implementations BMVC 2018 Ce Ge, Jingyu Wang, Qi Qi, Haifeng Sun, Jianxin Liao

As most weakly supervised object detection methods are based on pre-generated proposals, they often show two false detections: (i) group multiple object instances with one bounding box, and (ii) focus on only parts rather than the whole objects.

Semantic Segmentation Weakly Supervised Object Detection

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