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 501–550 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
Impossible Videos—0
Learning to Focus on the Foreground for Temporal Sentence Grounding—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
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
MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning—0
DenseImage Network: Video Spatial-Temporal Evolution Encoding and Understanding—0
AVD2: Accident Video Diffusion for Accident Video Description—0
How Well Can General Vision-Language Models Learn Medicine By Watching Public Educational Videos?—0
How to Make a BLT Sandwich? Learning to Reason towards Understanding Web Instructional Videos—0
Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network—0
MM-Ego: Towards Building Egocentric Multimodal LLMs—0
How Can Objects Help Video-Language Understanding?—0
H-MBA: Hierarchical MamBa Adaptation for Multi-Modal Video Understanding in Autonomous Driving—0
HLVU : A New Challenge to Test Deep Understanding of Movies the Way Humans do—0
Highlight Timestamp Detection Model for Comedy Videos via Multimodal Sentiment Analysis—0
Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding—0
Auto-X3D: Ultra-Efficient Video Understanding via Finer-Grained Neural Architecture Search—0
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning—0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation—0
HierarQ: Task-Aware Hierarchical Q-Former for Enhanced Video Understanding—0
Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training—0
AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark—0
Hierarchical Action Recognition: A Contrastive Video-Language Approach with Hierarchical Interactions—0
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition—0
Deep learning for action spotting in association football videos—0
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model—0
DANTE-AD: Dual-Vision Attention Network for Long-Term Audio Description—0
Action Reimagined: Text-to-Pose Video Editing for Dynamic Human Actions—0
Cycle-Contrast for Self-Supervised Video Representation Learning—0
A Unified Model for Video Understanding and Knowledge Embedding with Heterogeneous Knowledge Graph Dataset—0
HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions—0
Aggregating Frame-level Features for Large-Scale Video Classification—0
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