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 191–200 of 1149 papers

TitleStatusHype
M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object SegmentationCode1
MCAM: Multimodal Causal Analysis Model for Ego-Vehicle-Level Driving Video UnderstandingCode1
Crossover Learning for Fast Online Video Instance SegmentationCode1
Learning Transferable Spatiotemporal Representations from Natural Script KnowledgeCode1
Learning Temporally Latent Causal Processes from General Temporal DataCode1
Learning Temporally Causal Latent Processes from General Temporal DataCode1
CyberV: Cybernetics for Test-time Scaling in Video UnderstandingCode1
Learning the Predictability of the FutureCode1
Leveraging triplet loss for unsupervised action segmentationCode1
Learning Salient Boundary Feature for Anchor-free Temporal Action LocalizationCode1
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