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Liang Liao

4 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Liang Liao — 6 papers
  • Liang Liao — 4 papers
  • Liang Liao — 3 papers
  • Liang Liao — 1 paper
  • Liang Liao — 1 paper
  • Liang Liao — 1 paper

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

most citedImage Inpainting Guided by Coherence Priors of Semantics and Textures

8 citations · 11 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 1 cited

Neighbourhood Representative Sampling for Efficient End-to-end Video Quality Assessment

Haoning Wu, Chaofeng Chen, Liang Liao +5

The increased resolution of real-world videos presents a dilemma between efficiency and accuracy for deep Video Quality Assessment (VQA). On the one hand, keeping the original reso…

cs.CV2022★ 2 cited

Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning

Mengshun Hu, Kui Jiang, Liang Liao +3

Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate super-resolved videos with higher resolution(HR) and higher frame rate (HFR). Quite intuitively, pioneering two-st…

cs.CV2020★ 8 cited

Image Inpainting Guided by Coherence Priors of Semantics and Textures

Liang Liao, Jing Xiao, Zheng Wang +2

Existing inpainting methods have achieved promising performance in recovering defected images of specific scenes. However, filling holes involving multiple semantic categories rema…

cs.CV2020

Guidance and Evaluation: Semantic-Aware Image Inpainting for Mixed Scenes

Liang Liao, Jing Xiao, Zheng Wang +2

Completing a corrupted image with correct structures and reasonable textures for a mixed scene remains an elusive challenge. Since the missing hole in a mixed scene of a corrupted…

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