Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI
Vocal tract configurations play a vital role in generating distinguishable speech sounds, by modulating the airflow and creating different resonant cavities in speech production. They contain abundant information that ca…
Action RecognitionClassificationGeneral ClassificationTemporal Action Localization+1Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography
Electroencephalography (EEG) has become the most significant input signal for brain computer interface (BCI) based systems. However, it is very difficult to obtain satisfactory classification accuracy due to traditional …
Brain Computer InterfaceClassificationEEGElectroencephalogram (EEG)+3Deep Discriminative Model for Video Classification
This paper presents a new deep learning approach for video-based scene classification. We design a Heterogeneous Deep Discriminative Model (HDDM) whose parameters are initialized by performing an unsupervised pre-trainin…
Action RecognitionClassificationGeneral Classificationmodel+4Deep Architectures and Ensembles for Semantic Video Classification
This work addresses the problem of accurate semantic labelling of short videos. To this end, a multitude of different deep nets, ranging from traditional recurrent neural networks (LSTM, GRU), temporal agnostic networks …
ClassificationDiversityGeneral ClassificationVideo ClassificationAdversarial Perturbations Against Real-Time Video Classification Systems
Recent research has demonstrated the brittleness of machine learning systems to adversarial perturbations. However, the studies have been mostly limited to perturbations on images and more generally, classification that …
ClassificationGeneral ClassificationGenerative Adversarial NetworkVideo ClassificationA convex method for classification of groups of examples
There are many applications where it important to perform well on a set of examples as opposed to individual examples. For example in image or video classification the question is does an object appear somewhere in the i…
ClassificationGeneral Classificationglobal-optimizationimage-classification+3I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames
Over the past few years, various tasks involving videos such as classification, description, summarization and question answering have received a lot of attention. Current models for these tasks compute an encoding of th…
ClassificationGeneral ClassificationQuestion AnsweringVideo ClassificationVisual Data Synthesis via GAN for Zero-Shot Video Classification
Zero-Shot Learning (ZSL) in video classification is a promising research direction, which aims to tackle the challenge from explosive growth of video categories. Most existing methods exploit seen-to-unseen correlation v…
ClassificationGeneral ClassificationVideo ClassificationZero-Shot LearningBetter and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification
Video representation learning is a vital problem for classification task. Recently, a promising unsupervised paradigm termed self-supervised learning has emerged, which explores inherent supervisory signals implied in ma…
ClassificationGeneral ClassificationRepresentation LearningSelf-Supervised Learning+2Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos
In Actor and Observer we introduced a dataset linking the first and third-person video understanding domains, the Charades-Ego Dataset. In this paper we describe the egocentric aspect of the dataset and present annotatio…
General ClassificationVideo ClassificationVideo UnderstandingECO: Efficient Convolutional Network for Online Video Understanding
The state of the art in video understanding suffers from two problems: (1) The major part of reasoning is performed locally in the video, therefore, it misses important relationships within actions that span several seco…
Action ClassificationAction RecognitionGeneral ClassificationRetrieval+4On the effectiveness of task granularity for transfer learning
We describe a DNN for video classification and captioning, trained end-to-end, with shared features, to solve tasks at different levels of granularity, exploring the link between granularity in a source task and the qual…
ClassificationDiversityGeneral ClassificationTransfer Learning+1Walk-Steered Convolution for Graph Classification
Graph classification is a fundamental but challenging issue for numerous real-world applications. Despite recent great progress in image/video classification, convolutional neural networks (CNNs) cannot yet cater to grap…
ClassificationClusteringGeneral ClassificationGraph Classification+1Fine-grained Activity Recognition in Baseball Videos
In this paper, we introduce a challenging new dataset, MLB-YouTube, designed for fine-grained activity detection. The dataset contains two settings: segmented video classification as well as activity detection in continu…
Action DetectionActivity DetectionActivity RecognitionGeneral Classification+1Group Normalization
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Objectobject-detectionObject DetectionVideo ClassificationMLtuner: System Support for Automatic Machine Learning Tuning
MLtuner automatically tunes settings for training tunables (such as the learning rate, the momentum, the mini-batch size, and the data staleness bound) that have a significant impact on large-scale machine learning (ML) …
BIG-bench Machine LearningGeneral Classificationimage-classificationImage Classification+1Learning Representative Temporal Features for Action Recognition
In this paper, a novel video classification method is presented that aims to recognize different categories of third-person videos efficiently. Our motivation is to achieve a light model that could be trained with insuff…
Action RecognitionOptical Flow EstimationTemporal Action LocalizationTime Series+2Structured Label Inference for Visual Understanding
Visual data such as images and videos contain a rich source of structured semantic labels as well as a wide range of interacting components. Visual content could be assigned with fine-grained labels describing major comp…
Action DetectionGeneral Classificationimage-classificationImage Classification+3Deep-Temporal LSTM for Daily Living Action Recognition
In this paper, we propose to improve the traditional use of RNNs by employing a many to many model for video classification. We analyze the importance of modeling spatial layout and temporal encoding for daily living act…
Action RecognitionGeneral ClassificationOptical Flow EstimationTemporal Action Localization+1Neural Networks for irregularly observed continuous-time Stochastic Processes
Designing neural networks for continuous-time stochastic processes is challenging, especially when observations are made irregularly. In this article, we analyze neural networks from a frame theoretic perspective to iden…
Video Classification