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Video Understanding
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A crucial task of Video Understanding is to recognise and localise (in space and time) different actions or events appearing in the video.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges
VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding
UGC-VideoCaptioner: An Omni UGC Video Detail Caption Model and New Benchmarks
Chat with AI: The Surprising Turn of Real-time Video Communication from Human to AI
EmbRACE-3K: Embodied Reasoning and Action in Complex Environments
Video Event Reasoning and Prediction by Fusing World Knowledge from LLMs with Vision Foundation Models
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation
MCAM: Multimodal Causal Analysis Model for Ego-Vehicle-Level Driving Video Understanding
Omni-Video: Democratizing Unified Video Understanding and Generation
Kwai Keye-VL Technical Report
CAVALRY-V: A Large-Scale Generator Framework for Adversarial Attacks on Video MLLMs
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Flash-VStream: Efficient Real-Time Understanding for Long Video Streams
ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence Alignment
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs
Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs
Bridging Video Quality Scoring and Justification via Large Multimodal Models
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
Task-Aware KV Compression For Cost-Effective Long Video Understanding
PEVLM: Parallel Encoding for Vision-Language Models
GRPO-CARE: Consistency-Aware Reinforcement Learning for Multimodal Reasoning
video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language Models
InfiniPot-V: Memory-Constrained KV Cache Compression for Streaming Video Understanding
EVA02-AT: Egocentric Video-Language Understanding with Spatial-Temporal Rotary Positional Embeddings and Symmetric Optimization
MambaMia: A State-Space-Model-Based Compression for Efficient Video Understanding in Large Multimodal Models
AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understanding
EyeSim-VQA: A Free-Energy-Guided Eye Simulation Framework for Video Quality Assessment
Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation
Dual‑detector Re‑optimization for Federated Weakly Supervised Video Anomaly Detection Via Adaptive Dynamic Recursive Mapping
VideoDeepResearch: Long Video Understanding With Agentic Tool Using
HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person Scenarios
MLVTG: Mamba-Based Feature Alignment and LLM-Driven Purification for Multi-Modal Video Temporal Grounding
DiscoVLA: Discrepancy Reduction in Vision, Language, and Alignment for Parameter-Efficient Video-Text Retrieval
VersaVid-R1: A Versatile Video Understanding and Reasoning Model from Question Answering to Captioning Tasks
Super Encoding Network: Recursive Association of Multi-Modal Encoders for Video Understanding
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