Multi-Fiber Networks for Video Recognition (MFNet)

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Multi-Fiber Networks for Video Recognition (MFNet)

Motivation:减少时空网络的计算量,保持视频分类精度的基础上,使速度尽可能接近对应网络的2D版本. 为此提出 Multi-Fiber 网络,将复杂网络拆分成轻量网络的集成,利用 fibers 间的信息流引入多路器模块. Result:比I3D和R(2+1)D分别少9倍,13倍的计算量,但精度更高,UCF-101, HMDB-51 and Kinetics 上的 state of the art. 2D网络需要10s GFLOP来处理单帧,3D网络需要100s GFLOP处理一个clip,…

【ML】Two-Stream Convolutional Networks for Action Recognition in Videos

Two-Stream Convolutional Networks for Action Recognition in Videos & Towards Good Practices for Very Deep Two-Stream ConvNets Note here: it's a learning note on the topic of video representations. This note incorporates two papers about popular two-s…

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun The 13th European Conference on Computer Vision (ECCV), 2014 声明:本文所有图片均来自原始文章,自己的理解也未必正确,请查看原图并拍砖本文的两个亮点: 1. 多尺度训练CN…

目标检测--Spatial pyramid pooling in deep convolutional networks for visual recognition(PAMI, 2015)

Spatial pyramid pooling in deep convolutional networks for visual recognition 作者: Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun 引用: He, Kaiming, et al. "Spatial pyramid pooling in deep convolutional networks for visual recognition." IEEE…

PredNet --- Deep Predictive coding networks for video prediction and unsupervised learning --- 论文笔记

PredNet --- Deep Predictive coding networks for video prediction and unsupervised learning ICLR 2017 2017.03.12 Code and video examples can be found at: https://coxlab.github.io/prednet/ 摘要:基于监督训练的深度学习技术取得了非常大的成功,但是无监督问题仍然是一个未能解决的一大难题(从未标注的数据中学习到…

SPPNet论文翻译-空间金字塔池化Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

http://www.dengfanxin.cn/?p=403 原文地址我对物体检测的一篇重要著作SPPNet的论文的主要部分进行了翻译工作.SPPNet的初衷非常明晰,就是希望网络对输入的尺寸更加灵活,分析到卷积网络对尺寸并没有要求,固定尺寸的要求完全来源于全连接层部分,因而借助空间金字塔池化的方法来衔接两者,SPPNet在检测领域的重要贡献是避免了R-CNN的变形.重复计算等问题,在效果不衰减的情况下,大幅提高了识别速度. 用于视觉识别的深度卷积网络空间金字塔池化方法 Spatial…

Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition

Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition ICCV 2019 (oral) 2019-08-01 15:08:19 Paper:https://arxiv.org/abs/1907.13369 1. Backgroud and Motivation: 本文提出一种基于多智能体强化学习的未裁剪视频识别模型,来自适应的从未裁剪视频中,截取出样本视频…