Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
The increasing availability of traffic videos functioning on a 24/7/365 time scale has the great potential of increasing the spatio-temporal coverage of traffic accidents, which will help improve traffic safety. However,…
Large Language ModelMultimodal Large Language Modelobject-detectionObject Detection+2Towards Zero-Shot & Explainable Video Description by Reasoning over Graphs of Events in Space and Time
In the current era of Machine Learning, Transformers have become the de facto approach across a variety of domains, such as computer vision and natural language processing. Transformer-based solutions are the backbone of…
Object RecognitionText GenerationVideo ClassificationVideo DescriptionAn Empirical Study of Autoregressive Pre-training from Videos
We empirically study autoregressive pre-training from videos. To perform our study, we construct a series of autoregressive video models, called Toto. We treat videos as sequences of visual tokens and train transformer m…
Object TrackingVideo ClassificationTemporal Feature Weaving for Neonatal Echocardiographic Viewpoint Video Classification
Automated viewpoint classification in echocardiograms can help under-resourced clinics and hospitals in providing faster diagnosis and screening when expert technicians may not be available. We propose a novel approach t…
Classificationimage-classificationImage ClassificationVideo ClassificationCM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets
Challenges in cross-learning involve inhomogeneous or even inadequate amount of training data and lack of resources for retraining large pretrained models. Inspired by transfer learning techniques in NLP, adapters and pr…
Transfer LearningVideo ClassificationMulti-Modal Video Feature Extraction for Popularity Prediction
This work aims to predict the popularity of short videos using the videos themselves and their related features. Popularity is measured by four key engagement metrics: view count, like count, comment count, and share cou…
Feature EngineeringPredictionText GenerationVideo ClassificationDejaVid: Encoder-Agnostic Learned Temporal Matching for Video Classification
In recent years, large transformer-based video encoder models have greatly advanced state-of-the-art performance on video classification tasks. However, these large models typically process videos by averaging embedd…
Action ClassificationAction RecognitionFeature ImportanceTime Series Alignment+1AdaCM^2: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction
The advancements in large language models (LLMs) have propelled the improvement of video understanding tasks by incorporating LLMs with visual models. However, most existing LLM-based models (e.g., VideoLLaMA, VideoC…
GPUQuestion AnsweringVideo CaptioningVideo Classification+2LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning
Both few-shot learning and domain adaptation sub-fields in Computer Vision have seen significant recent progress in terms of the availability of state-of-the-art algorithms and datasets. Frameworks have been developed fo…
Domain AdaptationFew-Shot Learningimage-classificationImage Classification+4Gramian Multimodal Representation Learning and Alignment
Human perception integrates multiple modalities, such as vision, hearing, and language, into a unified understanding of the surrounding reality. While recent multimodal models have achieved significant progress by aligni…
Contrastive LearningRepresentation LearningText RetrievalVideo Classification+3Discrepancy-Aware Attention Network for Enhanced Audio-Visual Zero-Shot Learning
Audio-visual Zero-Shot Learning (ZSL) has attracted significant attention for its ability to identify unseen classes and perform well in video classification tasks. However, modal imbalance in (G)ZSL leads to over-relian…
Video ClassificationZero-Shot LearningContext-Aware Detection of Mixed Critical Events using Video Classification
Detecting mixed-critical events through computer vision is challenging due to the need for contextual understanding to assess event criticality accurately. Mixed critical events, such as fires of varying severity or traf…
Fire DetectionVideo ClassificationOccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under Occlusions
The lack of occlusion data in commonly used action recognition video datasets limits model robustness and impedes sustained performance improvements. We construct OccludeNet, a large-scale occluded video dataset that inc…
Action ClassificationAction RecognitionCausal Inferencecounterfactual+5AdaCM$^2$: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction
The advancements in large language models (LLMs) have propelled the improvement of video understanding tasks by incorporating LLMs with visual models. However, most existing LLM-based models (e.g., VideoLLaMA, VideoChat)…
GPUQuestion AnsweringVideo CaptioningVideo Classification+2Efficient Audio-Visual Fusion for Video Classification
We present Attend-Fusion, a novel and efficient approach for audio-visual fusion in video classification tasks. Our method addresses the challenge of exploiting both audio and visual modalities while maintaining a compac…
ClassificationVideo ClassificationAM Flow: Adapters for Temporal Processing in Action Recognition
Deep learning models, in particular \textit{image} models, have recently gained generalisability and robustness. %are becoming more general and robust by the day. In this work, we propose to exploit such advances in the …
Action ClassificationAction RecognitionTransfer LearningVideo ClassificationOptimizing Violence Detection in Video Classification Accuracy through 3D Convolutional Neural Networks
As violent crimes continue to happen, it becomes necessary to have security cameras that can rapidly identify moments of violence with excellent accuracy. The purpose of this study is to identify how many frames should b…
Optical Flow EstimationVideo ClassificationVideo Token Merging for Long-form Video Understanding
As the scale of data and models for video understanding rapidly expand, handling long-form video input in transformer-based models presents a practical challenge. Rather than resorting to input sampling or token dropping…
FormVideo ClassificationVideo UnderstandingDistributed Intelligent Video Surveillance for Early Armed Robbery Detection based on Deep Learning
Low employment rates in Latin America have contributed to a substantial rise in crime, prompting the emergence of new criminal tactics. For instance, "express robbery" has become a common crime committed by armed thieves…
object-detectionObject DetectionVideo ClassificationCPFD: Confidence-aware Privileged Feature Distillation for Short Video Classification
Dense features, customized for different business scenarios, are essential in short video classification. However, their complexity, specific adaptation requirements, and high computational costs make them resource-inten…
Video Classification