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Yuliang Liu

36 papers hereh-index 324.3k citations62 works total

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

author position
  • first author8
  • middle author27
  • last author1

Across the 36 of 36 papers where every author was matched, so the position is known.

fields
  • cs.CV35
  • cs.LG1
same name
  • Yuliang Liu — 40 papers, h 17
  • Yuliang Liu — 8 papers, h 4
  • Yuliang Liu — 7 papers, h 5
  • Yuliang Liu — 6 papers, h 3
  • Yuliang Liu — 4 papers, h 2
  • Yuliang Liu — 2 papers, h 4

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
20172025
most citedDetecting Curve Text in the Wild: New Dataset and New Solution

212 citations · 480 across the 34 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020★ 16 cited

Structured Multimodal Attentions for TextVQA

Chenyu Gao, Qi Zhu, Peng Wang +4

In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above. SMA first uses a structural graph represent…

cs.CV2020★ 13 cited

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering

Xinyu Wang, Yuliang Liu, Chunhua Shen +6

Visual Question Answering (VQA) methods have made incredible progress, but suffer from a failure to generalize. This is visible in the fact that they are vulnerable to learning coi…

cs.CV2020★ 37 cited

ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

Yuliang Liu, Hao Chen, Chunhua Shen +3

Scene text detection and recognition has received increasing research attention. Existing methods can be roughly categorized into two groups: character-based and segmentation-based…

cs.CV2020★ 4 cited

Separating Content from Style Using Adversarial Learning for Recognizing Text in the Wild

Canjie Luo, Qingxiang Lin, Yuliang Liu +2

We propose to improve text recognition from a new perspective by separating the text content from complex backgrounds. As vanilla GANs are not sufficiently robust to generate seque…

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