VETime: Vision Enhanced Zero-Shot Time Series Anomaly Detection

arXiv:2602.16681 · cs.CV · Submitted 2026-02-18 · Read on arXiv

cs.CV

Submitted: 2026-02-18

Updated: 2026-10-13

Code: https://github.com/yyyangcoder/VETime

Terminology

• Alignment — 3× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 6 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes

Sources

• Chronos: Learning the Language of Time Series
• TSPulse: Tiny Pre-Trained Models with Disentangled Representations for Rapid Time-Series Analysis
• Harnessing Vision-Language Models for Time Series Anomaly Detection
• Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
• Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives
• MLLM4TS: Leveraging Vision and Multimodal Language Models for General Time-Series Analysis
• Harnessing Vision Models for Time Series Analysis: A Survey
• Combinatorics of generalized orthogonal polynomials of type $R_{II}$
• Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
• SMIRK: 3D Facial Expressions through Analysis-by-Neural-Synthesis
• Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
• TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
• Can Multimodal LLMs Perform Time Series Anomaly Detection?
• Generalization of Modular Spread Complexity for Non-Hermitian Density Matrices
• Can LLMs Understand Time Series Anomalies?
• See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models