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 626–650 of 1149 papers

TitleStatusHype
3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation—0
A Backpack Full of Skills: Egocentric Video Understanding with Diverse Task Perspectives—0
Abductive Ego-View Accident Video Understanding for Safe Driving Perception—0
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition—0
Action Reimagined: Text-to-Pose Video Editing for Dynamic Human Actions—0
Action Sensitivity Learning for Temporal Action Localization—0
Action Understanding with Multiple Classes of Actors—0
Actor-Action Semantic Segmentation with Grouping Process Models—0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction—0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction—0
AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization—0
Adapting Pre-trained 3D Models for Point Cloud Video Understanding via Cross-frame Spatio-temporal Perception—0
Adaptive Intermediate Representations for Video Understanding—0
Adaptive Video Understanding Agent: Enhancing efficiency with dynamic frame sampling and feedback-driven reasoning—0
AdaTP: Attention-Debiased Token Pruning for Video Large Language Models—0
A Decade of Action Quality Assessment: Largest Systematic Survey of Trends, Challenges, and Future Directions—0
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems—0
Adversarial Robustness in RGB-Skeleton Action Recognition: Leveraging Attention Modality Reweighter—0
AE-Net:Adjoint Enhancement Network for Efficient Action Recognition in Video Understanding—0
AFO-TAD: Anchor-free One-Stage Detector for Temporal Action Detection—0
Aggregating Frame-level Features for Large-Scale Video Classification—0
AirLetters: An Open Video Dataset of Characters Drawn in the Air—0
Aligned Better, Listen Better for Audio-Visual Large Language Models—0
ALLVB: All-in-One Long Video Understanding Benchmark—0
AMEGO: Active Memory from long EGOcentric videos—0
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