Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence Alignment
We address the task of zero-shot fine-grained video classification, where no video examples or temporal annotations are available for unseen action classes. While contrastive vision-language models such as SigLIP demonst…
Dynamic Time WarpingLarge Language ModelOpen Set Learningtext similarity+2Exploring Audio Cues for Enhanced Test-Time Video Model Adaptation
Test-time adaptation (TTA) aims to boost the generalization capability of a trained model by conducting self-/unsupervised learning during the testing phase. While most existing TTA methods for video primarily utilize vi…
Test-time AdaptationVideo ClassificationSpatiotemporal Analysis of Forest Machine Operations Using 3D Video Classification
This paper presents a deep learning-based framework for classifying forestry operations from dashcam video footage. Focusing on four key work elements - crane-out, cutting-and-to-processing, driving, and processing - the…
Activity RecognitionVideo ClassificationVideo-GPT via Next Clip Diffusion
GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alternatively, the video sequence is good at…
DenoisingImage AnimationPredictionVideo Classification+4Read My Ears! Horse Ear Movement Detection for Equine Affective State Assessment
The Equine Facial Action Coding System (EquiFACS) enables the systematic annotation of facial movements through distinct Action Units (AUs). It serves as a crucial tool for assessing affective states in horses by identif…
Optical Flow EstimationVideo ClassificationPerception Encoder: The best visual embeddings are not at the output of the network
We introduce Perception Encoder (PE), a state-of-the-art encoder for image and video understanding trained via simple vision-language learning. Traditionally, vision encoders have relied on a variety of pretraining objec…
Depth EstimationLanguage ModelingLanguage ModellingObject Detection+2TenAd: A Tensor-based Low-rank Black Box Adversarial Attack for Video Classification
Deep learning models have achieved remarkable success in computer vision but remain vulnerable to adversarial attacks, particularly in black-box settings where model details are unknown. Existing adversarial attack metho…
Adversarial AttackVideo ClassificationUnbiasing through Textual Descriptions: Mitigating Representation Bias in Video Benchmarks
We propose a new "Unbiased through Textual Description (UTD)" video benchmark based on unbiased subsets of existing video classification and retrieval datasets to enable a more robust assessment of video understanding ca…
Common Sense ReasoningPredictionRetrievalVideo Classification+1Spatiotemporal Learning with Context-aware Video Tubelets for Ultrasound Video Analysis
Computer-aided pathology detection algorithms for video-based imaging modalities must accurately interpret complex spatiotemporal information by integrating findings across multiple frames. Current state-of-the-art metho…
object-detectionObject DetectionVideo ClassificationUltrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models
Ultrasound video classification enables automated diagnosis and has emerged as an important research area. However, publicly available ultrasound video datasets remain scarce, hindering progress in developing effective v…
ClassificationData AugmentationVideo ClassificationAccurate and Efficient Two-Stage Gun Detection in Video
Object detection in videos plays a crucial role in advancing applications such as public safety and anomaly detection. Existing methods have explored different techniques, including CNN, deep learning, and Transformers, …
Anomaly DetectionObjectobject-detectionObject Detection+1Online Meta-learning for AutoML in Real-time (OnMAR)
Automated machine learning (AutoML) is a research area focusing on using optimisation techniques to design machine learning (ML) algorithms, alleviating the need for a human to perform manual algorithm design. Real-time …
AutoMLImage ClusteringMeta-LearningVideo ClassificationVariable-frame CNNLSTM for Breast Nodule Classification using Ultrasound Videos
The intersection of medical imaging and artificial intelligence has become an important research direction in intelligent medical treatment, particularly in the analysis of medical images using deep learning for clinical…
ClassificationSpecificityVideo ClassificationOptimizing GPT for Video Understanding: Zero-Shot Performance and Prompt Engineering
In this study, we tackle industry challenges in video content classification by exploring and optimizing GPT-based models for zero-shot classification across seven critical categories of video quality. We contribute a no…
ClassificationPrompt EngineeringVideo ClassificationVideo Understanding+2Towards a Robust Framework for Multimodal Hate Detection: A Study on Video vs. Image-based Content
Social media platforms enable the propagation of hateful content across different modalities such as textual, auditory, and visual, necessitating effective detection methods. While recent approaches have shown promise in…
Hate Speech DetectionVideo ClassificationBRIDLE: Generalized Self-supervised Learning with Quantization
Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, reducing the reliance on large labeled datasets. Inspired by BERT's success in cap…
image-classificationImage ClassificationQuantizationSelf-Supervised Learning+1Extending Information Bottleneck Attribution to Video Sequences
We introduce VIBA, a novel approach for explainable video classification by adapting Information Bottlenecks for Attribution (IBA) to video sequences. While most traditional explainability methods are designed for image …
DeepFake DetectionFace SwappingOptical Flow EstimationVideo ClassificationDocument-Level Sentiment Analysis of Urdu Text Using Deep Learning Techniques
Document level Urdu Sentiment Analysis (SA) is a challenging Natural Language Processing (NLP) task as it deals with large documents in a resource-poor language. In large documents, there are ample amounts of words that …
Sentiment AnalysisVideo ClassificationWord EmbeddingsEfficient Lung Ultrasound Severity Scoring Using Dedicated Feature Extractor
With the advent of the COVID-19 pandemic, ultrasound imaging has emerged as a promising technique for COVID-19 detection, due to its non-invasive nature, affordability, and portability. In response, researchers have focu…
DiagnosticKnowledge DistillationSelf-Knowledge DistillationVideo ClassificationGenVidBench: A Challenging Benchmark for Detecting AI-Generated Video
The rapid advancement of video generation models has made it increasingly challenging to distinguish AI-generated videos from real ones. This issue underscores the urgent need for effective AI-generated video detectors t…
Video ClassificationVideo Generation