论文名称:SlowFast Networks for Video Recognition 论文地址:arxiv.org/abs/1812.0398 代码:github.com/facebookrese SlowFast算法原理 SlowFast是Facebook在2019年ICCV的一篇视频识别论文,受到灵长类动物的视网膜神经细胞种类的启发(大约80%的细胞(P-cells)以低频运作,可以识别细节信息;而大约20%的细胞(M-cells)则以...
论文地址:SlowFast Networks for Video Recognition 摘要 提出了用于视频分类的快慢结合的Two-Stream模型:(1)Slow网络,输入低帧率,用于提取空间语义信息;(2)Fast网络,输入高帧率,用于提取运动信息。因为,Fast网络的输入是高帧率的,为了减少计算量,作者设计成轻量级的Fast网络模型,减少了Fast网络的通道数。 1 引言 作者...
论文笔记:Gate-Shift Networks for Video Action Recognition(GSM) 代码链接: https://github.com/swathikirans/GSM 文章链接: https://arxiv.org/pdf/1912.00381.pdf 文章提出动机:当前视频行为识别各式各样,但没有达到像图像识别,ALexnet那样的效果。3D卷积参数多,计算量大...论文...
在众多的网络结构中,SlowFast Networks因其独特的双路径设计在视频识别任务中脱颖而出。本文将对SlowFast Networks进行深入的解析,并提供实践建议。 二、SlowFast Networks概述 SlowFast Networks由Facebook AI Research (FAIR)团队提出,其核心理念是结合慢速和快速两条路径来处理视频数据。慢速路径负责捕捉视频中的空间信息...
论文笔记:Gate-Shift Networks for Video Action Recognition(GSM) 代码链接: https://github.com/swathikirans/GSM 文章链接: https://arxiv.org/pdf/1912.00381.pdf 文章提出动机:当前视频行为识别各式各样,但没有达到像图像识别,ALexnet那样的效果。3D卷积参数多,计算量大... ...
We present SlowFast networks for video recognition. Our model involves (i) a Slow pathway, operating at low frame rate, to capture spatial semantics, and (ii) a Fast pathway, operating at high frame rate, to capture motion at fine temporal resolution. The Fast pathway can be made very ...
SlowFast Networks for Video Recognition Christoph Feichtenhofer Haoqi Fan Jitendra Malik Facebook AI Research (FAIR) Kaiming He Abstract We present SlowFast networks for video recognition. Our model involves (i) a Slow pathway, operating at low frame rate, to capture spatial semantics, and (ii) ...
SlowFast Networks是由Facebook AI Research(FAIR)提出的一种视频识别网络结构。该网络将视频帧分为两个流:slow流和fast流。slow流以较低的帧率运行,负责捕获空间语义信息;而fast流以较高的帧率运行,负责捕获运动信息。通过这种方式,SlowFast Networks能够在保持计算效率的同时,实现较高的视频识别准确率。 二、复现过程...
【基于slowfast的行为识别原理详解】SlowFast Networks for Video Recognition,我们准备尝试slowfast进行,从效果图上可以看出,其实read,run/jog类别的AP并不是很高。一种办法是我们重效果不是很好。
Action RecognitionH2O (2 Hands and Objects)SlowFastActions Top-177.69# 9 Compare RGBYes# 1 Compare Hand PoseNo# 1 Compare Object PoseNo# 1 Compare Object LabelNo# 1 Compare Action ClassificationKinetics-400SlowFast 16x8 (ResNet-101)Acc@178.9# 120 ...