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Yonghong Tian

4 papers here

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

author position
  • last author3

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

fields
  • cs.CV3
  • cs.LG1
ORCID 0000-0002-2978-5935
same name
  • Yonghong Tian — 88 papers, h 65
  • Yonghong Tian — 26 papers, h 24
  • Yonghong Tian — 25 papers, h 9
  • Yonghong Tian — 23 papers, h 9
  • Yonghong Tian — 22 papers, h 9
  • Yonghong Tian — 8 papers, h 7

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
20182024
most citedSelectivity or Invariance: Boundary-aware Salient Object Detection

20 citations · 27 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024★ 3 cited

EvaGaussians: Event Stream Assisted Gaussian Splatting from Blurry Images

Wangbo Yu, Chaoran Feng, Jiye Tang +6

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality,…

cs.LG2021★ 4 cited

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control

Liwen Zhu, Peixi Peng, Zongqing Lu +2

Traffic signal control aims to coordinate traffic signals across intersections to improve the traffic efficiency of a district or a city. Deep reinforcement learning (RL) has been…

cs.CV2018★ 20 cited

Selectivity or Invariance: Boundary-aware Salient Object Detection

Jinming Su, Jia Li, Yu Zhang +2

Typically, a salient object detection (SOD) model faces opposite requirements in processing object interiors and boundaries. The features of interiors should be invariant to strong…

cs.CV2018

Model-guided Multi-path Knowledge Aggregation for Aerial Saliency Prediction

Kui Fu, Jia Li, Yu Zhang +2

As an emerging vision platform, a drone can look from many abnormal viewpoints which brings many new challenges into the classic vision task of video saliency prediction. To invest…

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