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 291–300 of 1149 papers

TitleStatusHype
ReTaKe: Reducing Temporal and Knowledge Redundancy for Long Video UnderstandingCode1
MVTamperBench: Evaluating Robustness of Vision-Language Models—0
Perceive, Query & Reason: Enhancing Video QA with Question-Guided Temporal Queries—0
HumanVBench: Exploring Human-Centric Video Understanding Capabilities of MLLMs with Synthetic Benchmark Data—0
Video Domain Incremental Learning for Human Action Recognition in Home Environments—0
FriendsQA: A New Large-Scale Deep Video Understanding Dataset with Fine-grained Topic Categorization for Story VideosCode0
PruneVid: Visual Token Pruning for Efficient Video Large Language ModelsCode2
FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal GroundingCode1
InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language ModelsCode2
Do Language Models Understand Time?Code1
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