"Adversarial Augmentation Training Makes Action Recognition Models More ..."

Kiyoon Kim et al. (2024)

> Home

Details and statistics

DOI: 10.48550/ARXIV.2401.11406

access: open

type: Informal or Other Publication

metadata version: 2024-02-05

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/corr/abs-2401-11406
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2401-11406
Kiyoon Kim, Shreyank N. Gowda, Panagiotis Eustratiadis, Antreas Antoniou, Robert B. Fisher:
Adversarial Augmentation Training Makes Action Recognition Models More Robust to Realistic Video Distribution Shifts. CoRR abs/2401.11406 (2024)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.