TRUST is a scan-aware parameter-efficient image-to-video transfer learning framework for abdominal ultrasound trauma recognition featuring CFCA, MGMA, and VQSA modules that outperforms SOTA by 9.63% on in-house datasets.
A comprehensive study of deep video action recognition
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.CV 3verdicts
UNVERDICTED 3representative citing papers
AVATAAR reports relative gains of 5-8% over baseline on CinePile benchmark categories through agentic feedback for long video QA.
LA3D is a new lightweight method for video anonymization that improves privacy protection for crowd anomaly detection while maintaining detection performance better than existing approaches.
citing papers explorer
-
TRUST: Efficient Abdominal Trauma Recognition via Image-to-Ultrasound-Video Transfer Learning
TRUST is a scan-aware parameter-efficient image-to-video transfer learning framework for abdominal ultrasound trauma recognition featuring CFCA, MGMA, and VQSA modules that outperforms SOTA by 9.63% on in-house datasets.
-
AVATAAR: Agentic Video Answering via Temporal Adaptive Alignment and Reasoning
AVATAAR reports relative gains of 5-8% over baseline on CinePile benchmark categories through agentic feedback for long video QA.
-
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance
LA3D is a new lightweight method for video anonymization that improves privacy protection for crowd anomaly detection while maintaining detection performance better than existing approaches.