Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Video Representation Learning and Latent Concept Mining for Large-scale Multi-label Video Classification
We report on CMU Informedia Lab's system used in Google's YouTube 8 Million Video Understanding Challenge. In this multi-label video classification task, our pipeline achieved 84.675% and 84.662% GAP on our evaluation sp…
AttributeGeneral ClassificationRepresentation LearningVideo Classification+1Aggregating Frame-level Features for Large-Scale Video Classification
This paper introduces the system we developed for the Google Cloud & YouTube-8M Video Understanding Challenge, which can be considered as a multi-label classification problem defined on top of the large scale YouTube-8M …
ClassificationGeneral ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+2The YouTube-8M Kaggle Competition: Challenges and Methods
We took part in the YouTube-8M Video Understanding Challenge hosted on Kaggle, and achieved the 10th place within less than one month's time. In this paper, we present an extensive analysis and solution to the underlying…
General ClassificationVideo ClassificationVideo UnderstandingAn Effective Way to Improve YouTube-8M Classification Accuracy in Google Cloud Platform
Large-scale datasets have played a significant role in progress of neural network and deep learning areas. YouTube-8M is such a benchmark dataset for general multi-label video classification. It was created from over 7 m…
ClassificationDeep LearningGeneral ClassificationVideo Classification+1Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset
YouTube-8M is the largest video dataset for multi-label video classification. In order to tackle the multi-label classification on this challenging dataset, it is necessary to solve several issues such as temporal modeli…
ClassificationGeneral ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+1Multiresolution Match Kernels for Gesture Video Classification
The emergence of depth imaging technologies like the Microsoft Kinect has renewed interest in computational methods for gesture classification based on videos. For several years now, researchers have used the Bag-of-Feat…
ClassificationGeneral ClassificationVideo ClassificationLearnable pooling with Context Gating for video classification
Current methods for video analysis often extract frame-level features using pre-trained convolutional neural networks (CNNs). Such features are then aggregated over time e.g., by simple temporal averaging or more sophist…
ClassificationClusteringGeneral ClassificationVideo Classification+1Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text
The YouTube-8M video classification challenge requires teams to classify 0.7 million videos into one or more of 4,716 classes. In this Kaggle competition, we placed in the top 3% out of 650 participants using released vi…
ClassificationGeneral ClassificationVideo ClassificationThe Monkeytyping Solution to the YouTube-8M Video Understanding Challenge
This article describes the final solution of team monkeytyping, who finished in second place in the YouTube-8M video understanding challenge. The dataset used in this challenge is a large-scale benchmark for multi-label …
General ClassificationVideo ClassificationVideo UnderstandingHierarchical Label Inference for Video Classification
Videos are a rich source of high-dimensional structured data, with a wide range of interacting components at varying levels of granularity. In order to improve understanding of unconstrained internet videos, it is import…
ClassificationGeneral ClassificationVideo ClassificationModeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification
Videos are inherently multimodal. This paper studies the problem of how to fully exploit the abundant multimodal clues for improved video categorization. We introduce a hybrid deep learning framework that integrates usef…
General ClassificationVideo ClassificationLarge-Scale YouTube-8M Video Understanding with Deep Neural Networks
Video classification problem has been studied many years. The success of Convolutional Neural Networks (CNN) in image recognition tasks gives a powerful incentive for researchers to create more advanced video classificat…
ClassificationGeneral ClassificationMixture-of-ExpertsVideo Classification+1Temporal Segment Networks for Action Recognition in Videos
Deep convolutional networks have achieved great success for image recognition. However, for action recognition in videos, their advantage over traditional methods is not so evident. We present a general and flexible vide…
Action ClassificationAction RecognitionAction Recognition In VideosMicro-Action Recognition+2ActionVLAD: Learning spatio-temporal aggregation for action classification
In this work, we introduce a new video representation for action classification that aggregates local convolutional features across the entire spatio-temporal extent of the video. We do so by integrating state-of-the-art…
Action ClassificationClassificationGeneral ClassificationLong-video Activity Recognition+1TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition
Recent two-stream deep Convolutional Neural Networks (ConvNets) have made significant progress in recognizing human actions in videos. Despite their success, methods extending the basic two-stream ConvNet have not system…
Action ClassificationAction RecognitionActivity RecognitionTemporal Action Localization+2Saliency-guided video classification via adaptively weighted learning
Video classification is productive in many practical applications, and the recent deep learning has greatly improved its accuracy. However, existing works often model video frames indiscriminately, but from the view of m…
ClassificationGeneral ClassificationOptical Flow EstimationVideo ClassificationGraph-based Isometry Invariant Representation Learning
Learning transformation invariant representations of visual data is an important problem in computer vision. Deep convolutional networks have demonstrated remarkable results for image and video classification tasks. Howe…
General ClassificationRepresentation LearningTranslationVideo ClassificationDeep Motion Features for Visual Tracking
Robust visual tracking is a challenging computer vision problem, with many real-world applications. Most existing approaches employ hand-crafted appearance features, such as HOG or Color Names. Recently, deep RGB feature…
Action RecognitionOptical Flow EstimationTemporal Action LocalizationVideo Classification+1Generating Video Description using Sequence-to-sequence Model with Temporal Attention
Automatic video description generation has recently been getting attention after rapid advancement in image caption generation. Automatically generating description for a video is more challenging than for an image due t…
Caption GenerationSentenceVideo ClassificationVideo DescriptionDeep Temporal Linear Encoding Networks
The CNN-encoding of features from entire videos for the representation of human actions has rarely been addressed. Instead, CNN work has focused on approaches to fuse spatial and temporal networks, but these were typical…
Representation LearningVideo Classification