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

Showing 150 of 1149 papers

TitleStatusHype
CogVLM2: Visual Language Models for Image and Video UnderstandingCode9
World Model on Million-Length Video And Language With Blockwise RingAttentionCode9
Perception Encoder: The best visual embeddings are not at the output of the networkCode8
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningCode7
PerceptionLM: Open-Access Data and Models for Detailed Visual UnderstandingCode7
VideoRAG: Retrieval-Augmented Generation with Extreme Long-Context VideosCode7
InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingCode7
CVNets: High Performance Library for Computer VisionCode6
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video UnderstandingCode5
Segment Anything for Videos: A Systematic SurveyCode5
OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and UnderstandingCode5
ShareGPT4Video: Improving Video Understanding and Generation with Better CaptionsCode5
VideoMamba: State Space Model for Efficient Video UnderstandingCode5
Kwai Keye-VL Technical ReportCode4
VideoEval-Pro: Robust and Realistic Long Video Understanding EvaluationCode4
Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language ModelsCode4
VLog: Video-Language Models by Generative Retrieval of Narration VocabularyCode4
Unified Reward Model for Multimodal Understanding and GenerationCode4
Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video UnderstandingCode4
Video-XL: Extra-Long Vision Language Model for Hour-Scale Video UnderstandingCode4
Goldfish: Vision-Language Understanding of Arbitrarily Long VideosCode4
Tarsier: Recipes for Training and Evaluating Large Video Description ModelsCode4
PVUW 2024 Challenge on Complex Video Understanding: Methods and ResultsCode4
MovieChat+: Question-aware Sparse Memory for Long Video Question AnsweringCode4
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense CaptioningCode4
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual TokensCode4
SnAG: Scalable and Accurate Video GroundingCode4
An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsCode4
Video Understanding with Large Language Models: A SurveyCode4
A Survey on Video Diffusion ModelsCode4
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingCode4
VideoChat: Chat-Centric Video UnderstandingCode4
InternVideo: General Video Foundation Models via Generative and Discriminative LearningCode4
Flamingo: a Visual Language Model for Few-Shot LearningCode4
Flash-VStream: Efficient Real-Time Understanding for Long Video StreamsCode3
TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming VideosCode3
VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-TuningCode3
XAttention: Block Sparse Attention with Antidiagonal ScoringCode3
VideoMind: A Chain-of-LoRA Agent for Long Video ReasoningCode3
EgoLife: Towards Egocentric Life AssistantCode3
OpenTAD: A Unified Framework and Comprehensive Study of Temporal Action DetectionCode3
Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context AccurayCode3
VideoRoPE: What Makes for Good Video Rotary Position Embedding?Code3
Valley2: Exploring Multimodal Models with Scalable Vision-Language DesignCode3
VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLMCode3
VisionZip: Longer is Better but Not Necessary in Vision Language ModelsCode3
Towards Universal Soccer Video UnderstandingCode3
Video-RAG: Visually-aligned Retrieval-Augmented Long Video ComprehensionCode3
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language UnderstandingCode3
SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model InferenceCode3
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