论文题目:Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition 作者:Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh. National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba, Ibaraki, Japan 原文链接:https://arxiv.org/abs/1708.07632 代码链接:https://git...
最近参加了百度顶会论文复现营_AI学习 - 百度AI Studio - 一站式AI开发实训平台,本文是其中一篇论文解读的笔记。 论文:Learning Spatio-Temporal Features with 3D Residual Networks For Action Recognition 论文代码地址:github.com/kenshohara/3 课程介绍:由百度资深算法工程师与中科院高级研究员联合授课,28天手把手...
ResidualConvolutional neural network (CNN) is a natural structure for video modelling that has been successfully applied in the field of action recognition. The existing 3D CNN-based action recognition methods mainly perform 3D convolutions on individual cues (e.g. appearance and motion cues) and ...
In this work, we propose 3D Residual Attention Networks (3D RANs) for action recognition, which can learn spatiotemporal representation from videos. The proposed network consists of attention mechanism and 3D ResNets architecture, and it can capture spatiotemporal information in an end-to-end manner...
"Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition", Proceedings of the ICCV Workshop on Action, Gesture, and Emotion Recognition, 2017. This code includes training, fine-tuning and testing on Kinetics, Moments in Time, ActivityNet, UCF-101, and HMDB-51. Citati...
"Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition", Proceedings of the ICCV Workshop on Action, Gesture, and Emotion Recognition, 2017. This code includes only training and testing on the ActivityNet and Kinetics datasets. ...
paper题目:Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks paper是中国科学技术大学发表在ICCV 2017的工作 paper链接:地址 Abstract 卷积神经网络 (CNN) 是用于图像识别问题的一类强大的模型。然而,使用 CNN 学习时空视频表示,这并非易事。一些研究表明,执行 3D 卷积是一种捕获...
【论文复现PaddlePaddle】 # Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition(一)论文阅读 这篇文章是一篇2017ICCV ,该篇论文提出了一种基于2D ResNets 的3D ResNets网络结构。 卷积神经网络在动作识中有着较高的性能,基于CNN的动作识别的流行方... ...
【论文复现PaddlePaddle】 # Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition(一)论文阅读 这篇文章是一篇2017ICCV ,该篇论文提出了一种基于2D ResNets 的3D ResNets网络结构。 卷积神经网络在动作识中有着较高的性能,基于CNN的动作识别的流行方...猜...
一、前言 本文是“通过3D ResNet学习视频时空特征的行为识别(Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition)”论文和代码的学习笔记。 论文 https://arxiv.org/abs/1708…