Learning Temporal Evidence Selection for Video Anomaly Understanding
cs.CV
Submitted: 2026-10-12
Updated: 2026-10-12
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Video Anomaly Detection and Explanation via Large Language Models
- Recognize Anything: A Strong Image Tagging Model
- LLaVA-Video: Video Instruction Tuning With Synthetic Data
- Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
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