SOTAVerified

Video Understanding

A crucial task of Video Understanding is to recognise and localise (in space and time) different actions or events appearing in the video.

Source: Action Detection from a Robot-Car Perspective

Papers

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Showing 151–175 of 1149 papers

TitleStatusHype
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object SegmentationCode1
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster DistillationCode1
CyberV: Cybernetics for Test-time Scaling in Video UnderstandingCode1
SiLVR: A Simple Language-based Video Reasoning FrameworkCode1
VideoCAD: A Large-Scale Video Dataset for Learning UI Interactions and 3D Reasoning from CAD SoftwareCode1
DisTime: Distribution-based Time Representation for Video Large Language ModelsCode1
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?Code1
PreFM: Online Audio-Visual Event Parsing via Predictive Future ModelingCode1
VidText: Towards Comprehensive Evaluation for Video Text UnderstandingCode1
MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment GroundingCode1
Fact-R1: Towards Explainable Video Misinformation Detection with Deep ReasoningCode1
LoVR: A Benchmark for Long Video Retrieval in Multimodal ContextsCode1
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly DetectionCode1
TEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in ActionCode1
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video UnderstandingCode1
VideoMultiAgents: A Multi-Agent Framework for Video Question AnsweringCode1
IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMsCode1
VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video ModelsCode1
Multimodal Long Video Modeling Based on Temporal Dynamic ContextCode1
F^3Set: Towards Analyzing Fast, Frequent, and Fine-grained Events from VideosCode1
Slow-Fast Architecture for Video Multi-Modal Large Language ModelsCode1
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video UnderstandingCode1
PAVE: Patching and Adapting Video Large Language ModelsCode1
Exploring Hallucination of Large Multimodal Models in Video Understanding: Benchmark, Analysis and MitigationCode1
MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss AlpsCode1
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