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 476–500 of 1149 papers

TitleStatusHype
Slot State Space ModelsCode1
Hallucination Mitigation Prompts Long-term Video UnderstandingCode0
VideoVista: A Versatile Benchmark for Video Understanding and ReasoningCode1
VELOCITI: Benchmarking Video-Language Compositional Reasoning with Strict Entailment—0
Beyond Raw Videos: Understanding Edited Videos with Large Multimodal ModelCode0
Localizing Events in Videos with Multimodal Queries—0
GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding—0
LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living—0
Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMsCode2
VideoGPT+: Integrating Image and Video Encoders for Enhanced Video UnderstandingCode3
Flash-VStream: Memory-Based Real-Time Understanding for Long Video StreamsCode3
LVBench: An Extreme Long Video Understanding BenchmarkCode2
MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in VideosCode1
Fewer Tokens and Fewer Videos: Extending Video Understanding Abilities in Large Vision-Language Models—0
MeMSVD: Long-Range Temporal Structure Capturing Using Incremental SVD—0
Vript: A Video Is Worth Thousands of WordsCode2
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation—0
Semantic Segmentation on VSPW Dataset through Masked Video Consistency—0
ShareGPT4Video: Improving Video Understanding and Generation with Better CaptionsCode5
3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation—0
MLVU: Benchmarking Multi-task Long Video UnderstandingCode3
Contrastive Language Video Time Pre-training—0
Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric VideosCode1
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model—0
2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation—0
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