Papers Video Classification
“Video Classification” 태그가 달린 논문 495편 · 필터 해제
Unsupervised Meta-Learning For Few-Shot Image Classification
Few-shot or one-shot learning of classifiers requires a significant inductive bias towards the type of task to be learned. One way to acquire this is by meta-learning on tasks similar to the target task. In this paper, w…
ClassificationFew-Shot Image ClassificationFew-Shot LearningGeneral Classification+8Deep RNN Framework for Visual Sequential Applications
Extracting temporal and representation features efficiently plays a pivotal role in understanding visual sequence information. To deal with this, we propose a new recurrent neural framework that can be stacked deep effec…
Future predictionSSIMVideo ClassificationMulti-Task Learning of Generalizable Representations for Video Action Recognition
In classic video action recognition, labels may not contain enough information about the diverse video appearance and dynamics, thus, existing models that are trained under the standard supervised learning paradigm may e…
Action RecognitionMulti-Task LearningOptical Flow EstimationTemporal Action Localization+2Higher-order Network for Action Recognition
Capturing spatiotemporal dynamics is an essential topic in video recognition. In this paper, we present learnable higher-order operations as a generic family of building blocks for capturing spatiotemporal dynamics from …
Action RecognitionGeneral ClassificationVideo ClassificationVideo RecognitionNeXtVLAD: An Efficient Neural Network to Aggregate Frame-level Features for Large-scale Video Classification
This paper introduces a fast and efficient network architecture, NeXtVLAD, to aggregate frame-level features into a compact feature vector for large-scale video classification. Briefly speaking, the basic idea is to deco…
Efficient Neural NetworkGeneral ClassificationVideo ClassificationVideo UnderstandingCompact Generalized Non-local Network
The non-local module is designed for capturing long-range spatio-temporal dependencies in images and videos. Although having shown excellent performance, it lacks the mechanism to model the interactions between positions…
Object DetectionObject RecognitionVideo ClassificationCascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization
Weakly supervised temporal action localization, which aims at temporally locating action instances in untrimmed videos using only video-level class labels during training, is an important yet challenging problem in video…
Action LocalizationGeneral ClassificationTemporal Action LocalizationVideo Classification+1Fine-grained Video Categorization with Redundancy Reduction Attention
For fine-grained categorization tasks, videos could serve as a better source than static images as videos have a higher chance of containing discriminative patterns. Nevertheless, a video sequence could also contain a lo…
Action RecognitionVideo ClassificationTraining compact deep learning models for video classification using circulant matrices
In real world scenarios, model accuracy is hardly the only factor to consider. Large models consume more memory and are computationally more intensive, which makes them difficult to train and to deploy, especially on mob…
General ClassificationVideo ClassificationRepresentation Flow for Action Recognition
In this paper, we propose a convolutional layer inspired by optical flow algorithms to learn motion representations. Our representation flow layer is a fully-differentiable layer designed to capture the `flow' of any rep…
Action ClassificationAction RecognitionAction Recognition In VideosActivity Recognition+5Learnable Pooling Methods for Video Classification
We introduce modifications to state-of-the-art approaches to aggregating local video descriptors by using attention mechanisms and function approximations. Rather than using ensembles of existing architectures, we provid…
ClassificationGeneral ClassificationVideo ClassificationVideo UnderstandingNon-local NetVLAD Encoding for Video Classification
This paper describes our solution for the 2$^\text{nd}$ YouTube-8M video understanding challenge organized by Google AI. Unlike the video recognition benchmarks, such as Kinetics and Moments, the YouTube-8M challenge pro…
ClassificationGeneral ClassificationVideo ClassificationVideo Recognition+1Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks
Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs). However, when …
Action RecognitionClassificationGeneral ClassificationOptical Flow Estimation+2Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling
This paper presents the Axon AI's solution to the 2nd YouTube-8M Video Understanding Challenge, achieving the final global average precision (GAP) of 88.733% on the private test set (ranked 3rd among 394 teams, not consi…
General ClassificationVideo ClassificationVideo UnderstandingTowards Good Practices for Multi-modal Fusion in Large-scale Video Classification
Leveraging both visual frames and audio has been experimentally proven effective to improve large-scale video classification. Previous research on video classification mainly focuses on the analysis of visual content amo…
ClassificationGeneral ClassificationVideo ClassificationLabel Denoising with Large Ensembles of Heterogeneous Neural Networks
Despite recent advances in computer vision based on various convolutional architectures, video understanding remains an important challenge. In this work, we present and discuss a top solution for the large-scale video c…
Data AugmentationDenoisingGeneral ClassificationKnowledge Distillation+2Compound Memory Networks for Few-shot Video Classification
In this paper, we propose a new memory network structure for few-shot video classification by making the following contributions. First, we propose a compound memory network (CMN) structure under the key-value memory net…
ClassificationGeneral ClassificationVideo ClassificationApproach for Video Classification with Multi-label on YouTube-8M Dataset
Video traffic is increasing at a considerable rate due to the spread of personal media and advancements in media technology. Accordingly, there is a growing need for techniques to automatically classify moving images. Th…
General ClassificationVideo ClassificationIsometric Transformation Invariant Graph-based Deep Neural Network
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 ClassificationTranslationVideo ClassificationImproving Spatiotemporal Self-Supervision by Deep Reinforcement Learning
Self-supervised learning of convolutional neural networks can harness large amounts of cheap unlabeled data to train powerful feature representations. As surrogate task, we jointly address ordering of visual data in the …
Deep Reinforcement LearningGeneral Classificationreinforcement-learningReinforcement Learning+5