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 901–950 of 1149 papers

TitleStatusHype
Kill Two Birds With One Stone: Boosting Both Object Detection Accuracy and Speed With adaptive Patch-of-Interest Composition—0
KnowIT VQA: Answering Knowledge-Based Questions about Videos—0
Knowledge-Based Visual Question Answering in Videos—0
Koala: Key frame-conditioned long video-LLM—0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks—0
Language as the Medium: Multimodal Video Classification through text only—0
M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers—0
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges—0
Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling—0
Large Scale Video Representation Learning via Relational Graph Clustering—0
Large-Scale YouTube-8M Video Understanding with Deep Neural Networks—0
LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision—0
Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detection—0
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval—0
Learning Dynamic MRI Reconstruction with Convolutional Network Assisted Reconstruction Swin Transformer—0
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking—0
Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment—0
Learning from Multiple Sources for Video Summarisation—0
Learning Higher-order Object Interactions for Keypoint-based Video Understanding—0
Learning Object State Changes in Videos: An Open-World Perspective—0
Learning reusable concepts across different egocentric video understanding tasks—0
Learning Space-Time Semantic Correspondences—0
Learning text-to-video retrieval from image captioning—0
Learning to Focus on the Foreground for Temporal Sentence Grounding—0
Learning to Visually Connect Actions and their Effects—0
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition—0
Less than Few: Self-Shot Video Instance Segmentation—0
Leveraging Foundation Models for Multimodal Graph-Based Action Recognition—0
Leveraging Local Temporal Information for Multimodal Scene Classification—0
LIGAR: Lightweight General-purpose Action Recognition—0
LiveVLM: Efficient Online Video Understanding via Streaming-Oriented KV Cache and Retrieval—0
LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering—0
LLaVA-MLB: Mitigating and Leveraging Attention Bias for Training-Free Video LLMs—0
LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding—0
LLAVIDAL: A Large LAnguage VIsion Model for Daily Activities of Living—0
LLM4Brain: Training a Large Language Model for Brain Video Understanding—0
LLMs Meet Long Video: Advancing Long Video Question Answering with An Interactive Visual Adapter in LLMs—0
Localizing Events in Videos with Multimodal Queries—0
Localizing Unseen Activities in Video via Image Query—0
Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding—0
Long Activity Video Understanding using Functional Object-Oriented Network—0
LongCaptioning: Unlocking the Power of Long Caption Generation in Large Multimodal Models—0
Long-Short Temporal Contrastive Learning of Video Transformers—0
LongVILA: Scaling Long-Context Visual Language Models for Long Videos—0
LongViTU: Instruction Tuning for Long-Form Video Understanding—0
Long-VMNet: Accelerating Long-Form Video Understanding via Fixed Memory—0
Look Every Frame All at Once: Video-Ma^2mba for Efficient Long-form Video Understanding with Multi-Axis Gradient Checkpointing—0
Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization—0
LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents—0
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models—0
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