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Fei Wu

33 papers hereh-index 263.5k citations61 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author19
  • last author12

Across the 32 of 33 papers where every author was matched, so the position is known.

fields
  • cs.CL15
  • cs.CV14
  • cs.IR1
  • cs.LG1
  • cs.SI1
  • stat.ML1
same name
  • Fei Wu — 42 papers, h 59
  • Fei Wu — 17 papers
  • Fei Wu — 16 papers, h 23
  • Fei Wu — 15 papers, h 5
  • Fei Wu — 13 papers, h 6
  • Fei Wu — 11 papers, h 15

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182023
most citedDeVLBert: Learning Deconfounded Visio-Linguistic Representations

64 citations · 225 across the 19 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018

Bi-Adversarial Auto-Encoder for Zero-Shot Learning

Yunlong Yu, Zhong Ji, Yanwei Pang +3

Existing generative Zero-Shot Learning (ZSL) methods only consider the unidirectional alignment from the class semantics to the visual features while ignoring the alignment from th…

cs.IR2018

Textually Guided Ranking Network for Attentional Image Retweet Modeling

Zhou Zhao, Hanbing Zhan, Lingtao Meng +5

Retweet prediction is a challenging problem in social media sites (SMS). In this paper, we study the problem of image retweet prediction in social media, which predicts the image s…

cs.CV2018

Attentive Sequence to Sequence Translation for Localizing Clips of Interest by Natural Language Descriptions

Ke Ning, Linchao Zhu, Ming Cai +3

We propose a novel attentive sequence to sequence translator (ASST) for clip localization in videos by natural language descriptions. We make two contributions. First, we propose a…

cs.CV2018

Distribution-based Label Space Transformation for Multi-label Learning

Zongting Lyu, Yan Yan, Fei Wu

Multi-label learning problems have manifested themselves in various machine learning applications. The key to successful multi-label learning algorithms lies in the exploration of…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.