Adversarial Attack on Video Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Most implemented papers archive 2025-07-28

2 shown of 2 papers with code (2 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Prior-Guided Adversarial Initialization for Fast Adversarial Training
  18 Jul 2022 1 repository listed Syntology ran 2 of 4 samples · 2 unverified · 4 pointer-only (licence)
  Based on the observation, we propose a prior-guided FGSM initialization method to avoid overfitting after investigating several initialization strategies, improving the quality of the AEs during the whole training…
• Attacking Video Recognition Models with Bullet-Screen Comments
  29 Oct 2021 1 repository listed
  On both UCF-101 and HMDB-51 datasets, our BSC attack method can achieve about 90\% fooling rate when attacking three mainstream video recognition models, while only occluding \textless 8\% areas in the video.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.