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Chang Liu

8 papers hereh-index 6311 citations13 works total

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

author position
  • first author5
  • middle author3

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.MM2
  • cs.CR1
  • cs.LG1
same name
  • Chang Liu — 66 papers, h 39
  • Chang Liu — 38 papers, h 24
  • Chang Liu — 27 papers, h 20
  • Chang Liu — 23 papers, h 19
  • Chang Liu — 23 papers, h 22
  • Chang Liu — 22 papers, h 5

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
20192023
most citedHiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

136 citations · 196 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Transformer-empowered Multi-modal Item Embedding for Enhanced Image Search in E-Commerce

Chang Liu, Peng Hou, Anxiang Zeng +1

Over the past decade, significant advances have been made in the field of image search for e-commerce applications. Traditional image-to-image retrieval models, which focus solely…

cs.CV2021★ 6 cited

Noise-resistant Deep Metric Learning with Ranking-based Instance Selection

Chang Liu, Han Yu, Boyang Li +6

The existence of noisy labels in real-world data negatively impacts the performance of deep learning models. Although much research effort has been devoted to improving robustness…

cs.CV2020★ 41 cited

Towards Fine-grained Human Pose Transfer with Detail Replenishing Network

Lingbo Yang, Pan Wang, Chang Liu +7

Human pose transfer (HPT) is an emerging research topic with huge potential in fashion design, media production, online advertising and virtual reality. For these applications, the…

cs.CV2020★ 136 cited

HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

Lingbo Yang, Chang Liu, Pan Wang +4

Existing face restoration researches typically relies on either the degradation prior or explicit guidance labels for training, which often results in limited generalization abilit…

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