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Yong Liu

4 papers here

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CV4
ORCID 0000-0003-4454-1741
same name
  • Yong Liu — 25 papers
  • Yong Liu — 23 papers, h 16
  • Yong Liu — 19 papers, h 75
  • Yong Liu — 19 papers
  • Yong Liu — 18 papers
  • Yong Liu — 13 papers

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
20212024
most citedSOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation

14 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024

DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation

Haonan Lin, Mengmeng Wang, Yan Chen +6

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centered images, novel challenges arise with a nuanced task of "identity fine editi…

cs.CV2024★ 2 cited

SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking

Xiaojun Hou, Jiazheng Xing, Yijie Qian +8

Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness. Early research focused on fully fine-tuning RGB-based trackers, which was i…

cs.CV2023★ 14 cited

SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation

Zhuoyan Luo, Yicheng Xiao, Yong Liu +5

This paper studies referring video object segmentation (RVOS) by boosting video-level visual-linguistic alignment. Recent approaches model the RVOS task as a sequence prediction pr…

cs.CV2021

MSP : Refine Boundary Segmentation via Multiscale Superpixel

Jie Zhu, Huabin Huang, Banghuai Li +2

In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges…

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