most citedAdaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Cross-channel Perception Learning for H&E-to-IHC Virtual Staining

Hao Yang, JianYu Wu, Run Fang +7

With the rapid development of digital pathology, virtual staining has become a key technology in multimedia medical information systems, offering new possibilities for the analysis…

cs.CV20251 cited

Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning

Juncen Guo, Xiaoguang Zhu, Liangyu Teng +4

Class-incremental Learning (CIL) enables the model to incrementally absorb knowledge from new classes and build a generic classifier across all previously encountered classes. When…

cs.CV2025

CalFuse: Multi-Modal Continual Learning via Feature Calibration and Parameter Fusion

Juncen Guo, Siao Liu, Xiaoguang Zhu +8

With the proliferation of multi-modal data in large-scale visual recognition systems, enabling models to continuously acquire knowledge from evolving data streams while preserving…

cs.NI2025

A Survey on Video Analytics in Cloud-Edge-Terminal Collaborative Systems

Linxiao Gong, Hao Yang, Gaoyun Fang +7

The explosive growth of video data has driven the development of distributed video analytics in cloud-edge-terminal collaborative (CETC) systems, enabling efficient video processin…

cs.CV2024

Privacy-Preserving Video Anomaly Detection: A Survey

Yang Liu, Siao Liu, Xiaoguang Zhu +7

Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anomalous events that may cause harm…