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cs.CV2026
Probe-VAD: Ordinal Likelihood Probing for Training-Free Video Anomaly Detection
Jiawei Gu, Qilin Zhao, Tengkuo Guo +6
Video anomaly detection (VAD) aims to localize anomalous events in untrimmed videos. Vision-language models (VLMs) provide rich visual understanding for training-free VAD, but exis…
cs.CV2025
Beyond Background Shift: Rethinking Instance Replay in Continual Semantic Segmentation
Hongmei Yin, Tingliang Feng, Fan Lyu +4
In this work, we focus on continual semantic segmentation (CSS), where segmentation networks are required to continuously learn new classes without erasing knowledge of previously…
cs.CV2023
Long-Tailed Learning as Multi-Objective Optimization
Weiqi Li, Fan Lyu, Fanhua Shang +2
Real-world data is extremely imbalanced and presents a long-tailed distribution, resulting in models that are biased towards classes with sufficient samples and perform poorly on r…