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 501–525 of 1149 papers

TitleStatusHype
Inductive Attention for Video Action Anticipation—0
Discrete neural representations for explainable anomaly detection—0
Improving Video Model Transfer With Dynamic Representation Learning—0
Improving LLM Video Understanding with 16 Frames Per Second—0
Discerning Generic Event Boundaries in Long-Form Wild Videos—0
Action Understanding with Multiple Classes of Actors—0
MaxInfo: A Training-Free Key-Frame Selection Method Using Maximum Volume for Enhanced Video Understanding—0
Learning to Focus on the Foreground for Temporal Sentence Grounding—0
Impossible Videos—0
iMOVE: Instance-Motion-Aware Video Understanding—0
Identity-aware Graph Memory Network for Action Detection—0
Identifying Auxiliary or Adversarial Tasks Using Necessary Condition Analysis for Adversarial Multi-task Video Understanding—0
AirLetters: An Open Video Dataset of Characters Drawn in the Air—0
Action Sensitivity Learning for Temporal Action Localization—0
i-Code: An Integrative and Composable Multimodal Learning Framework—0
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding—0
Development of a MultiModal Annotation Framework and Dataset for Deep Video Understanding—0
Massively Parallel Video Networks—0
HuMoCon: Concept Discovery for Human Motion Understanding—0
HumanVBench: Exploring Human-Centric Video Understanding Capabilities of MLLMs with Synthetic Benchmark Data—0
Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection—0
HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
DenseImage Network: Video Spatial-Temporal Evolution Encoding and Understanding—0
AVD2: Accident Video Diffusion for Accident Video Description—0
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