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 801–825 of 1149 papers

TitleStatusHype
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges—0
Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling—0
Large Scale Video Representation Learning via Relational Graph Clustering—0
Large-Scale YouTube-8M Video Understanding with Deep Neural Networks—0
LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision—0
Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection—0
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking—0
Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment—0
Learning from Multiple Sources for Video Summarisation—0
Learning Higher-order Object Interactions for Keypoint-based Video Understanding—0
Learning Object State Changes in Videos: An Open-World Perspective—0
Learning reusable concepts across different egocentric video understanding tasks—0
Learning Space-Time Semantic Correspondences—0
Learning text-to-video retrieval from image captioning—0
Learning to Focus on the Foreground for Temporal Sentence Grounding—0
Learning to Visually Connect Actions and their Effects—0
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition—0
Less than Few: Self-Shot Video Instance Segmentation—0
Leveraging Foundation Models for Multimodal Graph-Based Action Recognition—0
Leveraging Local Temporal Information for Multimodal Scene Classification—0
LIGAR: Lightweight General-purpose Action Recognition—0
LiveVLM: Efficient Online Video Understanding via Streaming-Oriented KV Cache and Retrieval—0
LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering—0
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