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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 526–550 of 1149 papers

TitleStatusHype
Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric VisionCode0
LLaVA-OneVision: Easy Visual Task TransferCode0
METok: Multi-Stage Event-based Token Compression for Efficient Long Video UnderstandingCode0
MINOTAUR: Multi-task Video Grounding From Multimodal QueriesCode0
Masked Autoencoders for Egocentric Video Understanding @ Ego4D Challenge 2022Code0
A Challenge to Build Neuro-Symbolic Video AgentsCode0
Representation Flow for Action RecognitionCode0
Learning to Visually Connect Actions and their Effects—0
Learning to Focus on the Foreground for Temporal Sentence Grounding—0
Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey—0
Learning text-to-video retrieval from image captioning—0
Learning Space-Time Semantic Correspondences—0
An Effective Way to Improve YouTube-8M Classification Accuracy in Google Cloud Platform—0
Learning reusable concepts across different egocentric video understanding tasks—0
EAGLE: Egocentric AGgregated Language-video Engine—0
Learning Object State Changes in Videos: An Open-World Perspective—0
Learning Higher-order Object Interactions for Keypoint-based Video Understanding—0
Learning from Multiple Sources for Video Summarisation—0
DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding—0
BioVL-QR: Egocentric Biochemical Vision-and-Language Dataset Using Micro QR Codes—0
An Attempt towards Interpretable Audio-Visual Video Captioning—0
AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction—0
Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment—0
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking—0
DynFocus: Dynamic Cooperative Network Empowers LLMs with Video Understanding—0
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