Hi-GaTA is a hierarchical gated temporal aggregation adapter that uses short-to-long temporal pyramids and gated fusion to enable surgical video report generation, backed by a new 214-video benchmark and a surgical ViViT pretrained on 40,000 minutes of video.
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
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LATERN reformulates video anomaly detection as temporal evidence aggregation via context-aware scoring (CEA) and recursive aggregation (REA) to improve accuracy and coherence for frozen VLMs on benchmarks like UCF-Crime.
EgoSelf uses graph-based memory of user interactions to derive personalized profiles and predict future behaviors for egocentric assistants.
citing papers explorer
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Hi-GaTA: Hierarchical Gated Temporal Aggregation Adapter for Surgical Video Report Generation
Hi-GaTA is a hierarchical gated temporal aggregation adapter that uses short-to-long temporal pyramids and gated fusion to enable surgical video report generation, backed by a new 214-video benchmark and a surgical ViViT pretrained on 40,000 minutes of video.
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LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection
LATERN reformulates video anomaly detection as temporal evidence aggregation via context-aware scoring (CEA) and recursive aggregation (REA) to improve accuracy and coherence for frozen VLMs on benchmarks like UCF-Crime.
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EgoSelf: From Memory to Personalized Egocentric Assistant
EgoSelf uses graph-based memory of user interactions to derive personalized profiles and predict future behaviors for egocentric assistants.