A three-stage pipeline uses few-shot VLM action parsing, sliding-window segmentation, and LLM sequence classification with peer context to measure student engagement from classroom videos.
Two-stream con- volutional networks for action recognition in videos.Ad- vances in neural information processing systems, 27
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
-
Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification
A three-stage pipeline uses few-shot VLM action parsing, sliding-window segmentation, and LLM sequence classification with peer context to measure student engagement from classroom videos.