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researcher

Leida Li

16 papers hereh-index 457.3k citations245 works total

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

author position
  • middle author13
  • last author2

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • eess.IV2
  • cs.MM1
  • cs.NI1
same name
  • Leida Li — 10 papers, h 8
  • Leida Li — 5 papers, h 10
  • Leida Li — 3 papers, h 3
  • Leida Li — 1 paper
  • Leida Li — 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

activity
20172022
most citedSOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network

61 citations · 141 across the 12 of their papers we have counts for

collaborators
Showing 2021 · cs.CVShow all

4 papers · 2 filters

cs.CV2021

Robust Depth Completion with Uncertainty-Driven Loss Functions

Yufan Zhu, Weisheng Dong, Leida Li +3

Recovering a dense depth image from sparse LiDAR scans is a challenging task. Despite the popularity of color-guided methods for sparse-to-dense depth completion, they treated pixe…

cs.CV2021★ 61 cited

SOLVER: Scene-Object Interrelated Visual Emotion Reasoning Network

Jingyuan Yang, Xinbo Gao, Leida Li +2

Visual Emotion Analysis (VEA) aims at finding out how people feel emotionally towards different visual stimuli, which has attracted great attention recently with the prevalence of…

cs.CV2021★ 2 cited

StarVQA: Space-Time Attention for Video Quality Assessment

Fengchuang Xing, Yuan-Gen Wang, Hanpin Wang +2

The attention mechanism is blooming in computer vision nowadays. However, its application to video quality assessment (VQA) has not been reported. Evaluating the quality of in-the-…

cs.CV2021★ 4 cited

A Circular-Structured Representation for Visual Emotion Distribution Learning

Jingyuan Yang, Jie Li, Leida Li +2

Visual Emotion Analysis (VEA) has attracted increasing attention recently with the prevalence of sharing images on social networks. Since human emotions are ambiguous and subjectiv…

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