◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Xiaoming Liu

4 papers hereh-index 6270 citations7 works total

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
same name
  • Xiaoming Liu — 53 papers, h 70
  • Xiaoming Liu — 11 papers, h 6
  • Xiaoming Liu — 11 papers, h 7
  • Xiaoming Liu — 10 papers, h 5
  • Xiaoming Liu — 10 papers, h 3
  • Xiaoming Liu — 8 papers, h 14

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
20222024
most citedReverse Engineering of Imperceptible Adversarial Image Perturbations

8 citations · 11 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2024

UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models

Yihua Zhang, Chongyu Fan, Yimeng Zhang +8

The technological advancements in diffusion models (DMs) have demonstrated unprecedented capabilities in text-to-image generation and are widely used in diverse applications. Howev…

cs.CV2023

MaLP: Manipulation Localization Using a Proactive Scheme

Vishal Asnani, Xi Yin, Tal Hassner +1

Advancements in the generation quality of various Generative Models (GMs) has made it necessary to not only perform binary manipulation detection but also localize the modified pix…

cs.CV2023★ 3 cited

Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment

Yiyou Sun, Yaojie Liu, Xiaoming Liu +2

This work studies the generalization issue of face anti-spoofing (FAS) models on domain gaps, such as image resolution, blurriness and sensor variations. Most prior works regard do…

cs.CV2022★ 8 cited

Reverse Engineering of Imperceptible Adversarial Image Perturbations

Yifan Gong, Yuguang Yao, Yize Li +4

It has been well recognized that neural network based image classifiers are easily fooled by images with tiny perturbations crafted by an adversary. There has been a vast volume of…

◍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.