Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Fast Video Classification via Adaptive Cascading of Deep Models
Recent advances have enabled "oracle" classifiers that can classify across many classes and input distributions with high accuracy without retraining. However, these classifiers are relatively heavyweight, so that applyi…
ClassificationCPUDecision MakingGeneral Classification+3YouTube-8M: A Large-Scale Video Classification Benchmark
Many recent advancements in Computer Vision are attributed to large datasets. Open-source software packages for Machine Learning and inexpensive commodity hardware have reduced the barrier of entry for exploring novel ap…
3D Face ReconstructionAction RecognitionAction Recognition In VideosGeneral Classification+1Deep Learning for Video Classification and Captioning
Accelerated by the tremendous increase in Internet bandwidth and storage space, video data has been generated, published and spread explosively, becoming an indispensable part of today's big data. In this paper, we focus…
ClassificationDeep LearningGeneral ClassificationSentence+2DAiSEE: Towards User Engagement Recognition in the Wild
We introduce DAiSEE, the first multi-label video classification dataset comprising of 9068 video snippets captured from 112 users for recognizing the user affective states of boredom, confusion, engagement, and frustrati…
General ClassificationVideo ClassificationEfficient Two-Stream Motion and Appearance 3D CNNs for Video Classification
The video and action classification have extremely evolved by deep neural networks specially with two stream CNN using RGB and optical flow as inputs and they present outstanding performance in terms of video analysis. O…
3D ArchitectureAction ClassificationGeneral ClassificationOptical Flow Estimation+2Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition
Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data. Deep learning, although a break…
Action RecognitionAction Recognition In VideosGeneral Classificationimage-classification+3Discriminatively Trained Latent Ordinal Model for Video Classification
We study the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminati…
Action RecognitionClassificationGeneral Classificationmodel+4Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning
Encoding time-series with Linear Dynamical Systems (LDSs) leads to rich models with applications ranging from dynamical texture recognition to video segmentation to name a few. In this paper, we propose to represent LDSs…
Dictionary LearningGeneral ClassificationTime SeriesTime Series Analysis+3CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016
This paper presents the method that underlies our submission to the untrimmed video classification task of ActivityNet Challenge 2016. We follow the basic pipeline of temporal segment networks and further raise the perfo…
General ClassificationVideo ClassificationUntrimmed Video Classification for Activity Detection: submission to ActivityNet Challenge
Current state-of-the-art human activity recognition is focused on the classification of temporally trimmed videos in which only one action occurs per frame. We propose a simple, yet effective, method for the temporal det…
Action DetectionActivity DetectionActivity RecognitionBinary Classification+4Harnessing Object and Scene Semantics for Large-Scale Video Understanding
Large-scale action recognition and video categorization are important problems in computer vision. To address these problems, we propose a novel object- and scene-based semantic fusion network and representation. Our sem…
Action RecognitionClusteringObjectTemporal Action Localization+2Sparse Coding and Dictionary Learning With Linear Dynamical Systems
Linear Dynamical Systems (LDSs) are the fundamental tools for encoding spatio-temporal data in various disciplines. To enhance the performance of LDSs, in this paper, we address the challenging issue of performing sparse…
Dictionary LearningVideo ClassificationEvolution of active categorical image classification via saccadic eye movement
Pattern recognition and classification is a central concern for modern information processing systems. In particular, one key challenge to image and video classification has been that the computational cost of image proc…
ClassificationGeneral Classificationimage-classificationImage Classification+1Modelling Temporal Information Using Discrete Fourier Transform for Video Classification
Recently, video classification attracts intensive research efforts. However, most existing works are based on framelevel visual features, which might fail to model the temporal information, e.g. characteristics accumulat…
Action RecognitionClassificationEmotion ClassificationGeneral Classification+2Labeling the Features Not the Samples: Efficient Video Classification with Minimal Supervision
Feature selection is essential for effective visual recognition. We propose an efficient joint classifier learning and feature selection method that discovers sparse, compact representations of input features from a vast…
Clusteringfeature selectionGeneral ClassificationVideo ClassificationDeep End2End Voxel2Voxel Prediction
Over the last few years deep learning methods have emerged as one of the most prominent approaches for video analysis. However, so far their most successful applications have been in the area of video classification and …
Neural Architecture SearchOptical Flow EstimationPredictionSemantic Segmentation+2Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks
One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter- and intra-subject differences, as well as to inherent noise associated with …
EEGElectroencephalogram (EEG)General ClassificationTime Series+2Handcrafted Local Features are Convolutional Neural Networks
Image and video classification research has made great progress through the development of handcrafted local features and learning based features. These two architectures were proposed roughly at the same time and have f…
Action RecognitionOptical Flow EstimationTemporal Action LocalizationVideo ClassificationFusing Multi-Stream Deep Networks for Video Classification
This paper studies deep network architectures to address the problem of video classification. A multi-stream framework is proposed to fully utilize the rich multimodal information in videos. Specifically, we first train …
ClassificationGeneral ClassificationVideo ClassificationBeyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video
Recent studies have demonstrated the power of recurrent neural networks for machine translation, image captioning and speech recognition. For the task of capturing temporal structure in video, however, there still remain…
Gesture RecognitionImage CaptioningMachine Translationspeech-recognition+3