ViewBridge uses curriculum knowledge distillation and a geometry-based occlusion metric to learn view-invariant activity representations from multi-view training data, outperforming prior methods on keystep grounding and recognition across three datasets from single-view inference.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2verdicts
UNVERDICTED 2representative citing papers
PIE-V is a framework that injects plausible mistakes and corrections into egocentric procedural videos via psychology-informed planning and LLM-assisted video synthesis, paired with a nine-metric human rubric for benchmarking.
citing papers explorer
-
ViewBridge: Curriculum Knowledge Distillation for Activity View-Invariance Under Extreme Viewpoint Changes
ViewBridge uses curriculum knowledge distillation and a geometry-based occlusion metric to learn view-invariant activity representations from multi-view training data, outperforming prior methods on keystep grounding and recognition across three datasets from single-view inference.
-
How to Correctly Make Mistakes: A Framework for Constructing and Benchmarking Mistake Aware Egocentric Procedural Videos
PIE-V is a framework that injects plausible mistakes and corrections into egocentric procedural videos via psychology-informed planning and LLM-assisted video synthesis, paired with a nine-metric human rubric for benchmarking.