CREST uses local curvature of query-frame relevance over time to select informative frames, outperforming a lightweight baseline and approaching a costly pipeline at far lower preprocessing cost on long-video benchmarks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
CREST: Curvature-Regulated Event-Centric Sampling for Efficient Long-Video Understanding
CREST uses local curvature of query-frame relevance over time to select informative frames, outperforming a lightweight baseline and approaching a costly pipeline at far lower preprocessing cost on long-video benchmarks.