Saved in:
| Main Authors: | Zhao, Zihao, Cao, Shengting, Ye, Muchao |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.01004 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection
by: Piehl, Mitchell, et al.
Published: (2026)
by: Piehl, Mitchell, et al.
Published: (2026)
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models
by: Ye, Muchao, et al.
Published: (2024)
by: Ye, Muchao, et al.
Published: (2024)
SatBLIP: Context Understanding and Feature Identification from Satellite Imagery with Vision-Language Learning
by: Wu, Xue, et al.
Published: (2026)
by: Wu, Xue, et al.
Published: (2026)
CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World
by: Yu, Yating, et al.
Published: (2025)
by: Yu, Yating, et al.
Published: (2025)
VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning
by: Zhu, Liyun, et al.
Published: (2025)
by: Zhu, Liyun, et al.
Published: (2025)
ESOM: Efficiently Understanding Streaming Video Anomalies with Open-world Dynamic Definitions
by: Liu, Zihao, et al.
Published: (2026)
by: Liu, Zihao, et al.
Published: (2026)
Understanding Real-World Traffic Safety through RoadSafe365 Benchmark
by: Liu, Xinyu, et al.
Published: (2026)
by: Liu, Xinyu, et al.
Published: (2026)
Shot-Aware Frame Sampling for Video Understanding
by: Zhao, Mengyu, et al.
Published: (2026)
by: Zhao, Mengyu, et al.
Published: (2026)
Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought
by: Huang, Chao, et al.
Published: (2025)
by: Huang, Chao, et al.
Published: (2025)
Hawk: Learning to Understand Open-World Video Anomalies
by: Tang, Jiaqi, et al.
Published: (2024)
by: Tang, Jiaqi, et al.
Published: (2024)
EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO
by: Guan, Wei, et al.
Published: (2025)
by: Guan, Wei, et al.
Published: (2025)
LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding
by: Qiu, Jihao, et al.
Published: (2026)
by: Qiu, Jihao, et al.
Published: (2026)
VideoTG-R1: Boosting Video Temporal Grounding via Curriculum Reinforcement Learning on Reflected Boundary Annotations
by: Dong, Lu, et al.
Published: (2025)
by: Dong, Lu, et al.
Published: (2025)
VADER: Towards Causal Video Anomaly Understanding with Relation-Aware Large Language Models
by: Cheng, Ying, et al.
Published: (2025)
by: Cheng, Ying, et al.
Published: (2025)
AD-DINOv3: Enhancing DINOv3 for Zero-Shot Anomaly Detection with Anomaly-Aware Calibration
by: Yuan, Jingyi, et al.
Published: (2025)
by: Yuan, Jingyi, et al.
Published: (2025)
AI-Generated Video Detection via Spatio-Temporal Anomaly Learning
by: Bai, Jianfa, et al.
Published: (2024)
by: Bai, Jianfa, et al.
Published: (2024)
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2024)
by: Yin, Ziyi, et al.
Published: (2024)
Incentivizing Temporal-Awareness in Egocentric Video Understanding Models
by: Xu, Zhiyang, et al.
Published: (2026)
by: Xu, Zhiyang, et al.
Published: (2026)
TAU-R1: Visual Language Model for Traffic Anomaly Understanding
by: Lin, Yuqiang, et al.
Published: (2026)
by: Lin, Yuqiang, et al.
Published: (2026)
Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection
by: Tao, Chenchen, et al.
Published: (2024)
by: Tao, Chenchen, et al.
Published: (2024)
Text-guided Fine-Grained Video Anomaly Understanding
by: Gu, Jihao, et al.
Published: (2025)
by: Gu, Jihao, et al.
Published: (2025)
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning
by: Zhao, Shifang, et al.
Published: (2025)
by: Zhao, Shifang, et al.
Published: (2025)
CurveStream: Boosting Streaming Video Understanding in MLLMs via Curvature-Aware Hierarchical Visual Memory Management
by: Wang, Chao, et al.
Published: (2026)
by: Wang, Chao, et al.
Published: (2026)
Language-guided Open-world Video Anomaly Detection under Weak Supervision
by: Liu, Zihao, et al.
Published: (2025)
by: Liu, Zihao, et al.
Published: (2025)
TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning
by: Wu, Tao, et al.
Published: (2025)
by: Wu, Tao, et al.
Published: (2025)
Video Anomaly Detection with Semantics-Aware Information Bottleneck
by: Li, Juntong, et al.
Published: (2025)
by: Li, Juntong, et al.
Published: (2025)
Rethinking Metrics and Benchmarks of Video Anomaly Detection
by: Liu, Zihao, et al.
Published: (2025)
by: Liu, Zihao, et al.
Published: (2025)
Prototypical Learning Guided Context-Aware Segmentation Network for Few-Shot Anomaly Detection
by: Jiang, Yuxin, et al.
Published: (2025)
by: Jiang, Yuxin, et al.
Published: (2025)
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
by: Meng, Desen, et al.
Published: (2025)
by: Meng, Desen, et al.
Published: (2025)
Enhancing Scene Transition Awareness in Video Generation via Post-Training
by: Shen, Hanwen, et al.
Published: (2025)
by: Shen, Hanwen, et al.
Published: (2025)
HierarQ: Task-Aware Hierarchical Q-Former for Enhanced Video Understanding
by: Azad, Shehreen, et al.
Published: (2025)
by: Azad, Shehreen, et al.
Published: (2025)
Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection
by: Pu, Yujiang, et al.
Published: (2023)
by: Pu, Yujiang, et al.
Published: (2023)
VADTree: Explainable Training-Free Video Anomaly Detection via Hierarchical Granularity-Aware Tree
by: Li, Wenlong, et al.
Published: (2025)
by: Li, Wenlong, et al.
Published: (2025)
AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP
by: Ma, Wenxin, et al.
Published: (2025)
by: Ma, Wenxin, et al.
Published: (2025)
Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
VisionCreator-R1: A Reflection-Enhanced Native Visual-Generation Agentic Model
by: Lai, Jinxiang, et al.
Published: (2026)
by: Lai, Jinxiang, et al.
Published: (2026)
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
by: Tao, Fenfang, et al.
Published: (2024)
by: Tao, Fenfang, et al.
Published: (2024)
PA-CLIP: Enhancing Zero-Shot Anomaly Detection through Pseudo-Anomaly Awareness
by: Pan, Yurui, et al.
Published: (2025)
by: Pan, Yurui, et al.
Published: (2025)
Ground-R1: Incentivizing Grounded Visual Reasoning via Reinforcement Learning
by: Cao, Meng, et al.
Published: (2025)
by: Cao, Meng, et al.
Published: (2025)
VideoMem: Enhancing Ultra-Long Video Understanding via Adaptive Memory Management
by: Jin, Hongbo, et al.
Published: (2025)
by: Jin, Hongbo, et al.
Published: (2025)
Similar Items
-
LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection
by: Piehl, Mitchell, et al.
Published: (2026) -
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models
by: Ye, Muchao, et al.
Published: (2024) -
SatBLIP: Context Understanding and Feature Identification from Satellite Imagery with Vision-Language Learning
by: Wu, Xue, et al.
Published: (2026) -
CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World
by: Yu, Yating, et al.
Published: (2025) -
VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning
by: Zhu, Liyun, et al.
Published: (2025)