◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Yong-Liang Yang

4 papers hereh-index 5120 citations6 works total

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

author position
  • middle author3

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

fields
  • cs.CV4
same name
  • Yong-Liang Yang — 2 papers, h 0
  • Yong-Liang Yang — 2 papers, h 6
  • Yong-Liang Yang — 2 papers
  • Yong-Liang Yang — 1 paper, h 1
  • Yong-Liang Yang — 1 paper, h 3
  • Yong-Liang Yang — 1 paper, 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
20192022
most citedUnderstanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack

8 citations · 9 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2022★ 1 cited

Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack

Yunfeng Diao, He Wang, Tianjia Shao +4

Human Activity Recognition (HAR) has been employed in a wide range of applications, e.g. self-driving cars, where safety and lives are at stake. Recently, the robustness of skeleto…

cs.CV2021★ 8 cited

Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack

He Wang, Feixiang He, Zhexi Peng +4

Action recognition has been heavily employed in many applications such as autonomous vehicles, surveillance, etc, where its robustness is a primary concern. In this paper, we exami…

cs.CV2021

BASAR:Black-box Attack on Skeletal Action Recognition

Yunfeng Diao, Tianjia Shao, Yong-Liang Yang +2

Skeletal motion plays a vital role in human activity recognition as either an independent data source or a complement. The robustness of skeleton-based activity recognizers has bee…

cs.CV2019

SMART: Skeletal Motion Action Recognition aTtack

He Wang, Feixiang He, Zhexi Peng +4

Adversarial attack has inspired great interest in computer vision, by showing that classification-based solutions are prone to imperceptible attack in many tasks. In this paper, we…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.