ENTITY
VideoMAE-v2
VideoMAE-v2
PulseAugur coverage of VideoMAE-v2 — every cluster mentioning VideoMAE-v2 across labs, papers, and developer communities, ranked by signal.
Total · 30d
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Papers · 30d
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TIER MIX · 90D
TOPICS
SENTIMENT · 30D
1 day(s) with sentiment data
RECENT · PAGE 1/1 · 2 TOTAL
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VAGNet uses global features for real-time accident anticipation
Researchers have developed VAGNet, a novel deep neural network designed to anticipate traffic accidents using global features from dash-cam video. Unlike previous methods that rely on computationally intensive object-le…
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VideoMAE-v2 approach anticipates traffic accidents in zero-shot setting
Researchers have developed a new zero-shot approach for anticipating traffic accidents using dashcam footage. Their method, which couples a VideoMAE-v2 backbone with a per-frame prediction head, can predict imminent col…