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 31–40 of 1149 papers

TitleStatusHype
MLVTG: Mamba-Based Feature Alignment and LLM-Driven Purification for Multi-Modal Video Temporal Grounding—0
Super Encoding Network: Recursive Association of Multi-Modal Encoders for Video Understanding—0
SurgBench: A Unified Large-Scale Benchmark for Surgical Video Analysis—0
SceneRAG: Scene-level Retrieval-Augmented Generation for Video Understanding—0
CyberV: Cybernetics for Test-time Scaling in Video UnderstandingCode1
Bridging Audio and Vision: Zero-Shot Audiovisual Segmentation by Connecting Pretrained Models—0
Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric VisionCode0
APVR: Hour-Level Long Video Understanding with Adaptive Pivot Visual Information Retrieval—0
TextVidBench: A Benchmark for Long Video Scene Text Understanding—0
DualX-VSR: Dual Axial SpatialTemporal Transformer for Real-World Video Super-Resolution without Motion Compensation—0
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