{"task":"Anomaly Detection","dataset":"UCF-Crime","metric_names":["AUC"],"rows":[{"id":655613,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"MM-VAD","metrics":{"AUC":"98.81"},"paper_url":"https://paperswithcode.com/paper/geometry-aware-semantic-reasoning-for-training-free-video-anomaly-detection","paper_title":"Geometry-Aware Semantic Reasoning for Training Free Video Anomaly Detection","paper_date":"2026-03-10","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655552,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"VANGUARD","metrics":{"AUC":"94"},"paper_url":"https://paperswithcode.com/paper/reasoning-guided-grounding-elevating-video-anomaly-detection-through-multimodal-large-language-models","paper_title":"Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models","paper_date":"2026-04-07","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655969,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"Gaussian","metrics":{"AUC":"91.58"},"paper_url":"https://paperswithcode.com/paper/mixture-of-experts-guided-by-gaussian-splatters-matters-a-new-approach-to-weakly-supervised-video-anomaly-detection","paper_title":"Mixture of Experts Guided by Gaussian Splatters Matters: A new Approach to Weakly-Supervised Video Anomaly Detection","paper_date":"2025-08-08","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655816,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"TRACES","metrics":{"AUC":"90.4"},"paper_url":"https://paperswithcode.com/paper/traces-temporal-recall-with-contextual-embeddings-for-real-time-video-anomaly-detection","paper_title":"TRACES: Temporal Recall with Contextual Embeddings for Real-Time Video Anomaly Detection","paper_date":"2025-11-01","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655587,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"DeSC","metrics":{"AUC":"89.37"},"paper_url":"https://paperswithcode.com/paper/decoupled-sensitivity-consistency-learning-for-weakly-supervised-video-anomaly-detection","paper_title":"Decoupled Sensitivity-Consistency Learning for Weakly Supervised Video Anomaly Detection","paper_date":"2026-03-20","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655442,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"VigilFormer","metrics":{"AUC":"87.83"},"paper_url":"https://paperswithcode.com/paper/vigilformer-deformable-attention-for-video-anomaly-detection-with-causal-risk-inference","paper_title":"VigilFormer: Deformable Attention for Video Anomaly Detection with Causal Risk Inference","paper_date":"2026-05-31","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":655752,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"PA-VAD","metrics":{"AUC":"82.5"},"paper_url":"https://paperswithcode.com/paper/pa-vad-diffusion-based-pseudo-only-video-anomaly-detection-via-domain-aligned-memory-updates","paper_title":"PA-VAD: Diffusion-Based Pseudo-Only Video Anomaly Detection via Domain-Aligned Memory Updates","paper_date":"2025-12-07","code_links":[],"metrics_order":null,"area":null,"uses_additional_data":null,"source":"auto","tags":[]},{"id":19776,"task":"Anomaly Detection","parent_task":null,"dataset":"UCF-Crime","model_name":"MULDE-frame-centric-micro-one-class-classification","metrics":{"AUC":"78.5%"},"paper_url":"https://arxiv.org/abs/2403.14497v1","paper_title":"MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection","paper_date":"2024-03-21","code_links":[{"title":"jakubmicorek/MULDE-Multiscale-Log-Density-Estimation-via-Denoising-Score-Matching-for-Video-Anomaly-Detection","url":"https://github.com/jakubmicorek/MULDE-Multiscale-Log-Density-Estimation-via-Denoising-Score-Matching-for-Video-Anomaly-Detection"}],"metrics_order":"[\"AUC\"]","area":"Methodology","uses_additional_data":0,"source":"archive","tags":[]}]}