Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)
Understanding Activities of Daily Living (ADLs) is a crucial step for different applications including assistive robots, smart homes, and healthcare. However, to date, few benchmarks and methods have focused on complex A…
Few Shot Action RecognitionFine-Grained Image ClassificationFine-Grained Visual RecognitionVideo ClassificationToxVidLM: A Multimodal Framework for Toxicity Detection in Code-Mixed Videos
In an era of rapidly evolving internet technology, the surge in multimodal content, including videos, has expanded the horizons of online communication. However, the detection of toxic content in this diverse landscape, …
Video ClassificationDeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark
Recently, video generation techniques have advanced rapidly. Given the popularity of video content on social media platforms, these models intensify concerns about the spread of fake information. Therefore, there is a gr…
DeepFake DetectionMambaVideo ClassificationVideo Generation+2SIAVC: Semi-Supervised Framework for Industrial Accident Video Classification
Semi-supervised learning suffers from the imbalance of labeled and unlabeled training data in the video surveillance scenario. In this paper, we propose a new semi-supervised learning method called SIAVC for industrial a…
Fire DetectionModel OptimizationPseudo LabelVideo ClassificationA Survey on Visual Mamba
State space models (SSMs) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently demonstrated significant promise in long-sequence modeling. Since the self-attention mechanism in transfor…
Image RegistrationImage RestorationImage Super-ResolutionMamba+6MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding
With the success of large language models (LLMs), integrating the vision model into LLMs to build vision-language foundation models has gained much more interest recently. However, existing LLM-based large multimodal mod…
GPUMultiple-choiceQuestion AnsweringTemporal Relation Extraction+5Learning Correlation Structures for Vision Transformers
We introduce a new attention mechanism, dubbed structural self-attention (StructSA), that leverages rich correlation patterns naturally emerging in key-query interactions of attention. StructSA generates attention maps b…
Action ClassificationAction RecognitionObjectVideo ClassificationX-MIC: Cross-Modal Instance Conditioning for Egocentric Action Generalization
Lately, there has been growing interest in adapting vision-language models (VLMs) to image and third-person video classification due to their success in zero-shot recognition. However, the adaptation of these models to e…
Video ClassificationZero-Shot LearningRobustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning
We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classification (…
Classificationimage-classificationImage ClassificationReinforcement Learning (RL)+1Pig aggression classification using CNN, Transformers and Recurrent Networks
The development of techniques that can be used to analyze and detect animal behavior is a crucial activity for the livestock sector, as it is possible to monitor the stress and animal welfare and contributes to decision …
ClassificationVideo ClassificationLeveraging Compressed Frame Sizes For Ultra-Fast Video Classification
Classifying videos into distinct categories, such as Sport and Music Video, is crucial for multimedia understanding and retrieval, especially when an immense volume of video content is being constantly generated. Traditi…
Dynamic Time WarpingRetrievalVideo ClassificationLearning Expressive And Generalizable Motion Features For Face Forgery Detection
Previous face forgery detection methods mainly focus on appearance features, which may be easily attacked by sophisticated manipulation. Considering the majority of current face manipulation methods generate fake faces b…
Anomaly DetectionClassificationVideo ClassificationA Multimodal Handover Failure Detection Dataset and Baselines
An object handover between a robot and a human is a coordinated action which is prone to failure for reasons such as miscommunication, incorrect actions and unexpected object properties. Existing works on handover failur…
Action SegmentationObjectTemporal Action SegmentationVideo ClassificationMulti-modality transrectal ultrasound video classification for identification of clinically significant prostate cancer
Prostate cancer is the most common noncutaneous cancer in the world. Recently, multi-modality transrectal ultrasound (TRUS) has increasingly become an effective tool for the guidance of prostate biopsies. With the aim of…
Video ClassificationVideo Annotator: A framework for efficiently building video classifiers using vision-language models and active learning
High-quality and consistent annotations are fundamental to the successful development of robust machine learning models. Traditional data annotation methods are resource-intensive and inefficient, often leading to a reli…
Active LearningVideo ClassificationVideo UnderstandingTime-, Memory- and Parameter-Efficient Visual Adaptation
As foundation models become more popular, there is a growing need to efficiently finetune them for downstream tasks. Although numerous adaptation methods have been proposed, they are designed to be efficient only in term…
GPUVideo ClassificationFakeClaim: A Multiple Platform-driven Dataset for Identification of Fake News on 2023 Israel-Hamas War
We contribute the first publicly available dataset of factual claims from different platforms and fake YouTube videos on the 2023 Israel-Hamas war for automatic fake YouTube video classification. The FakeClaim data is co…
Fact CheckingLanguage ModelingLanguage ModellingSentence+1Short-Form Videos and Mental Health: A Knowledge-Guided Neural Topic Model
Along with the rise of short-form videos, their mental impacts on viewers have led to widespread consequences, prompting platforms to predict videos' impact on viewers' mental health. Subsequently, they can take interven…
FormTopic ModelsVideo ClassificationEfficient Multiscale Multimodal Bottleneck Transformer for Audio-Video Classification
In recent years, researchers combine both audio and video signals to deal with challenges where actions are not well represented or captured by visual cues. However, how to effectively leverage the two modalities is stil…
GPURepresentation LearningVideo ClassificationEfficient Selective Audio Masked Multimodal Bottleneck Transformer for Audio-Video Classification
Audio and video are two most common modalities in the mainstream media platforms, e.g., YouTube. To learn from multimodal videos effectively, in this work, we propose a novel audio-video recognition approach termed audio…
Action RecognitionContrastive LearningVideo ClassificationVideo Recognition