Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Billion-scale semi-supervised learning for image classification
This paper presents a study of semi-supervised learning with large convolutional networks. We propose a pipeline, based on a teacher/student paradigm, that leverages a large collection of unlabelled images (up to 1 billi…
ClassificationGeneral Classificationimage-classificationImage Classification+2MANIFOLDNET: A DEEP NEURAL NETWORK FOR MANIFOLD-VALUED DATA
Developing deep neural networks (DNNs) for manifold-valued data sets has gained much interest of late in the deep learning research community. Examples of manifold-valued data include data from omnidirectional cameras o…
General ClassificationImage ReconstructionVideo ClassificationThe Expressive Power of Deep Neural Networks with Circulant Matrices
Recent results from linear algebra stating that any matrix can be decomposed into products of diagonal and circulant matrices has lead to the design of compact deep neural network architectures that perform well in pract…
General ClassificationVideo ClassificationWhere and when to look? Spatial-temporal attention for action recognition in videos
Inspired by the observation that humans are able to process videos efficiently by only paying attention when and where it is needed, we propose a novel spatial-temporal attention mechanism for video-based action recognit…
Action RecognitionAction Recognition In VideosTemporal Action LocalizationVideo ClassificationFactor Analysis in Fault Diagnostics Using Random Forest
Factor analysis or sometimes referred to as variable analysis has been extensively used in classification problems for identifying specific factors that are significant to particular classes. This type of analysis has be…
AttributeClusteringFault DiagnosisGeneral Classification+1Large Scale Holistic Video Understanding
Video recognition has been advanced in recent years by benchmarks with rich annotations. However, research is still mainly limited to human action or sports recognition - focusing on a highly specific video understanding…
Action ClassificationAction RecognitionMulti-Task LearningRepresentation Learning+5DynamoNet: Dynamic Action and Motion Network
In this paper, we are interested in self-supervised learning the motion cues in videos using dynamic motion filters for a better motion representation to finally boost human action recognition in particular. Thus far, th…
Action RecognitionClassificationGeneral ClassificationMulti-Task Learning+3Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis
Higher-order data with high dimensionality arise in a diverse set of application areas such as computer vision, video analytics and medical imaging. Tensors provide a natural tool for representing these types of data. Al…
ClassificationGeneral ClassificationTensor DecompositionVideo ClassificationSelf-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
We address the problem of video representation learning without human-annotated labels. While previous efforts address the problem by designing novel self-supervised tasks using video data, the learned features are merel…
Action RecognitionGeneral ClassificationRepresentation LearningSelf-Supervised Action Recognition+1Video Classification with Channel-Separated Convolutional Networks
Group convolution has been shown to offer great computational savings in various 2D convolutional architectures for image classification. It is natural to ask: 1) if group convolution can help to alleviate the high compu…
Action ClassificationAction RecognitionGeneral Classificationimage-classification+2Robust Real-Time Violence Detection in Video Using CNN And LSTM
Detection of a violence event in surveillance systems is playing a significant role in law enforcement and city safety. The effectiveness of violence event detectors measures by the speed of response and the accuracy and…
Action Recognition In VideosVideo ClassificationVideo-based surgical skill assessment using 3D convolutional neural networks
Purpose: A profound education of novice surgeons is crucial to ensure that surgical interventions are effective and safe. One important aspect is the teaching of technical skills for minimally invasive or robot-assisted …
Action Quality AssessmentSurgical Skills EvaluationVideo ClassificationSemantic Adversarial Network with Multi-scale Pyramid Attention for Video Classification
Two-stream architecture have shown strong performance in video classification task. The key idea is to learn spatio-temporal features by fusing convolutional networks spatially and temporally. However, there are some pro…
ClassificationGeneral ClassificationOptical Flow EstimationVideo ClassificationEfficient Video Classification Using Fewer Frames
Recently,there has been a lot of interest in building compact models for video classification which have a small memory footprint (<1 GB). While these models are compact, they typically operate by repeated application of…
ClassificationClusteringGeneral ClassificationVideo ClassificationSaliency Tubes: Visual Explanations for Spatio-Temporal Convolutions
Deep learning approaches have been established as the main methodology for video classification and recognition. Recently, 3-dimensional convolutions have been used to achieve state-of-the-art performance in many challen…
Action ClassificationGeneral ClassificationVideo ClassificationUnderstanding and Training Deep Diagonal Circulant Neural Networks
In this paper, we study deep diagonal circulant neural networks, that is deep neural networks in which weight matrices are the product of diagonal and circulant ones. Besides making a theoretical analysis of their expres…
Video ClassificationAdversarial Framing for Image and Video Classification
Neural networks are prone to adversarial attacks. In general, such attacks deteriorate the quality of the input by either slightly modifying most of its pixels, or by occluding it with a patch. In this paper, we propose …
ClassificationGeneral ClassificationVideo ClassificationTimeception for Complex Action Recognition
This paper focuses on the temporal aspect for recognizing human activities in videos; an important visual cue that has long been undervalued. We revisit the conventional definition of activity and restrict it to Complex …
Action ClassificationAction RecognitionLong-video Activity RecognitionVideo ClassificationMS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language
Sign language recognition is a challenging and often underestimated problem comprising multi-modal articulators (handshape, orientation, movement, upper body and face) that integrate asynchronously on multiple streams. L…
Action RecognitionSign Language RecognitionTemporal Action LocalizationVideo ClassificationDeep Multimodal Learning: An Effective Method for Video Classification
Videos have become ubiquitous on the Internet. And video analysis can provide lots of information for detecting and recognizing objects as well as help people understand human actions and interactions with the real world…
ClassificationGeneral ClassificationLanguage ModelingLanguage Modelling+3