most citedFPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework

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cs.CV2026

FeedbackTrack: Visual-Cortex-Inspired Cross-Frame Feedback for Transformer Tracking

Yueyang Cang, Xiaoteng Zhang, Zhiyuan Ning +2

Visual object tracking requires effective temporal integration, yet most Transformer trackers still rely on predominantly feed-forward feature extraction. Existing temporal mechani…

cs.CV2026

PRIMED: Adaptive Modality Suppression for Referring Audio-Visual Segmentation via Biased Competition

Yuchen He, Jing Zhang

Referring Audio-Visual Segmentation (Ref-AVS) seeks to localize and segment target objects in video frames based on visual, auditory, and textual referring cues. The task is challe…

cs.CV2024

Masked Autoencoders are Parameter-Efficient Federated Continual Learners

Yuchen He, Xiangfeng Wang

Federated learning is a specific distributed learning paradigm in which a central server aggregates updates from multiple clients' local models, thereby enabling the server to lear…