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 401–425 of 1149 papers

TitleStatusHype
From Seconds to Hours: Reviewing MultiModal Large Language Models on Comprehensive Long Video UnderstandingCode1
EAGLE: Egocentric AGgregated Language-video Engine—0
E.T. Bench: Towards Open-Ended Event-Level Video-Language UnderstandingCode2
LLM4Brain: Training a Large Language Model for Brain Video Understanding—0
Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP—0
Video-XL: Extra-Long Vision Language Model for Hour-Scale Video UnderstandingCode4
Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder—0
First Place Solution to the Multiple-choice Video QA Track of The Second Perception Test Challenge—0
Interpretable Action Recognition on Hard to Classify Actions—0
AMEGO: Active Memory from long EGOcentric videos—0
HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions—0
SoccerNet 2024 Challenges ResultsCode0
Enhancing Long Video Understanding via Hierarchical Event-Based Memory—0
VidLPRO: A Video-Language Pre-training Framework for Robotic and Laparoscopic Surgery—0
TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations—0
LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid ArchitectureCode3
VideoLLaMB: Long-context Video Understanding with Recurrent Memory Bridges—0
StimuVAR: Spatiotemporal Stimuli-aware Video Affective Reasoning with Multimodal Large Language Models—0
Streamlining Forest Wildfire Surveillance: AI-Enhanced UAVs Utilizing the FLAME Aerial Video Dataset for Lightweight and Efficient Monitoring—0
DLM-VMTL:A Double Layer Mapper for heterogeneous data video Multi-task prompt learning—0
CogVLM2: Visual Language Models for Image and Video UnderstandingCode9
Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input—0
Video-CCAM: Enhancing Video-Language Understanding with Causal Cross-Attention Masks for Short and Long VideosCode2
Attend-Fusion: Efficient Audio-Visual Fusion for Video Classification—0
LMM-VQA: Advancing Video Quality Assessment with Large Multimodal ModelsCode0
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