◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Di Huang

4 papers hereh-index 6465 citations9 works total

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.CV4
same name
  • Di Huang — 44 papers, h 20
  • Di Huang — 28 papers, h 10
  • Di Huang — 20 papers, h 39
  • Di Huang — 16 papers, h 12
  • Di Huang — 16 papers, h 6
  • Di Huang — 14 papers, h 12

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
20212025
most citedStudent-Teacher Feature Pyramid Matching for Anomaly Detection

106 citations · 127 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025★ 1 cited

Towards Training-free Anomaly Detection with Vision and Language Foundation Models

Jinjin Zhang, Guodong Wang, Yizhou Jin +1

Anomaly detection is valuable for real-world applications, such as industrial quality inspection. However, most approaches focus on detecting local structural anomalies while negle…

cs.CV2023

Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection

Guodong Wang, Yunhong Wang, Jie Qin +3

Anomaly detection (AD), aiming to find samples that deviate from the training distribution, is essential in safety-critical applications. Though recent self-supervised learning bas…

cs.CV2023★ 20 cited

Align-DETR: Enhancing End-to-end Object Detection with Aligned Loss

Zhi Cai, Songtao Liu, Guodong Wang +3

DETR has set up a simple end-to-end pipeline for object detection by formulating this task as a set prediction problem, showing promising potential. Despite its notable advancement…

cs.CV2021★ 106 cited

Student-Teacher Feature Pyramid Matching for Anomaly Detection

Guodong Wang, Shumin Han, Errui Ding +1

Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies. This paper proposes a simple yet powerful appro…

◍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.