Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
A Unified Method for First and Third Person Action Recognition
In this paper, a new video classification methodology is proposed which can be applied in both first and third person videos. The main idea behind the proposed strategy is to capture complementary information of appearan…
Action RecognitionGeneral ClassificationOptical Flow EstimationTemporal Action Localization+3Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification
Despite the steady progress in video analysis led by the adoption of convolutional neural networks (CNNs), the relative improvement has been less drastic as that in 2D static image classification. Three main challenges e…
Action ClassificationAction DetectionAction RecognitionClassification+5Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks
Convolutional Neural Networks (CNN) have been regarded as a powerful class of models for image recognition problems. Nevertheless, it is not trivial when utilizing a CNN for learning spatio-temporal video representation.…
Action RecognitionPhilosophyvalidVideo ClassificationAttention Clusters: Purely Attention Based Local Feature Integration for Video Classification
Recently, substantial research effort has focused on how to apply CNNs or RNNs to better extract temporal patterns from videos, so as to improve the accuracy of video classification. In this paper, however, we show that …
ClassificationGeneral ClassificationVideo ClassificationAppearance-and-Relation Networks for Video Classification
Spatiotemporal feature learning in videos is a fundamental problem in computer vision. This paper presents a new architecture, termed as Appearance-and-Relation Network (ARTNet), to learn video representation in an end-t…
Action ClassificationAction RecognitionClassificationGeneral Classification+4Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification
The work in this paper is driven by the question how to exploit the temporal cues available in videos for their accurate classification, and for human action recognition in particular? Thus far, the vision community has …
Action RecognitionGeneral ClassificationTemporal Action LocalizationTransfer Learning+1Non-local Neural Networks
Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-rang…
Action ClassificationAction RecognitionInstance SegmentationKeypoint Detection+5Attend and Interact: Higher-Order Object Interactions for Video Understanding
Human actions often involve complex interactions across several inter-related objects in the scene. However, existing approaches to fine-grained video understanding or visual relationship detection often rely on single o…
Action ClassificationAction RecognitionObjectRelationship Detection+6Two-stream Collaborative Learning with Spatial-Temporal Attention for Video Classification
Video classification is highly important with wide applications, such as video search and intelligent surveillance. Video naturally consists of static and motion information, which can be represented by frame and optical…
General ClassificationOptical Flow EstimationVideo ClassificationVocal Bursts Valence PredictionEnd-to-End Video Classification with Knowledge Graphs
Video understanding has attracted much research attention especially since the recent availability of large-scale video benchmarks. In this paper, we address the problem of multi-label video classification. We first obse…
BIG-bench Machine LearningClassificationGeneral ClassificationKnowledge Graphs+2Convolutional Drift Networks for Video Classification
Analyzing spatio-temporal data like video is a challenging task that requires processing visual and temporal information effectively. Convolutional Neural Networks have shown promise as baseline fixed feature extractors …
ClassificationGeneral ClassificationTransfer LearningVideo ClassificationMulti-modal Aggregation for Video Classification
In this paper, we present a solution to Large-Scale Video Classification Challenge (LSVC2017) [1] that ranked the 1st place. We focused on a variety of modalities that cover visual, motion and audio. Also, we visualized …
ClassificationGeneral ClassificationVideo ClassificationVideo Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor
We investigate video classification via a two-stream convolutional neural network (CNN) design that directly ingests information extracted from compressed video bitstreams. Our approach begins with the observation that a…
ClassificationCloud ComputingCPUGeneral Classification+3Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API
Due to the growth of video data on Internet, automatic video analysis has gained a lot of attention from academia as well as companies such as Facebook, Twitter and Google. In this paper, we examine the robustness of vid…
Video ClassificationRevisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification
This paper describes our solution for the video recognition task of ActivityNet Kinetics challenge that ranked the 1st place. Most of existing state-of-the-art video recognition approaches are in favor of an end-to-end p…
Action ClassificationGeneral ClassificationVideo ClassificationVideo RecognitionUTS submission to Google YouTube-8M Challenge 2017
In this paper, we present our solution to Google YouTube-8M Video Classification Challenge 2017. We leveraged both video-level and frame-level features in the submission. For video-level classification, we simply used a …
ClassificationGeneral ClassificationMixture-of-ExpertsVideo ClassificationLarge-scale Video Classification guided by Batch Normalized LSTM Translator
Youtube-8M dataset enhances the development of large-scale video recognition technology as ImageNet dataset has encouraged image classification, recognition and detection of artificial intelligence fields. For this large…
ClassificationGeneral Classificationimage-classificationImage Classification+3Hierarchical Deep Recurrent Architecture for Video Understanding
This paper introduces the system we developed for the Youtube-8M Video Understanding Challenge, in which a large-scale benchmark dataset was used for multi-label video classification. The proposed framework contains hier…
ClassificationGeneral ClassificationMixture-of-ExpertsVideo Classification+1A spatiotemporal model with visual attention for video classification
High level understanding of sequential visual input is important for safe and stable autonomy, especially in localization and object detection. While traditional object classification and tracking approaches are specific…
ClassificationGeneral ClassificationObjectobject-detection+2Tensor-Train Recurrent Neural Networks for Video Classification
The Recurrent Neural Networks and their variants have shown promising performances in sequence modeling tasks such as Natural Language Processing. These models, however, turn out to be impractical and difficult to train …
ClassificationGeneral ClassificationVideo Classification