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 1126–1149 of 1149 papers

TitleStatusHype
Large-Scale YouTube-8M Video Understanding with Deep Neural Networks—0
Deep Learning Methods for Efficient Large Scale Video LabelingCode0
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition—0
Action Understanding with Multiple Classes of Actors—0
Video Object Segmentation using Supervoxel-Based GerrymanderingCode0
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity RecognitionCode0
Temporal Tessellation: A Unified Approach for Video AnalysisCode0
Real-Time Video Highlights for Yahoo Esports—0
Generating Videos with Scene Dynamics—0
VideoMCC: a New Benchmark for Video Comprehension—0
Slicing Convolutional Neural Network for Crowd Video Understanding—0
MSR-VTT: A Large Video Description Dataset for Bridging Video and Language—0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding—0
The THUMOS Challenge on Action Recognition for Videos "in the Wild"—0
The Open World of Micro-Videos—0
Actor-Action Semantic Segmentation with Grouping Process Models—0
Mid-level Representation for Visual Recognition—0
Fine-Grain Annotation of Cricket Videos—0
Person Count Localization in Videos From Noisy Foreground and Detections—0
Unsupervised Object Discovery and Tracking in Video Collections—0
Learning from Multiple Sources for Video Summarisation—0
Pooled Motion Features for First-Person VideosCode0
Weakly Supervised Multiclass Video Segmentation—0
Grounding Action Descriptions in Videos—0
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