文章的3D ResNet比具有相对较浅架构的C3D具有更高的精度。 表2 Kinetics数据集的准确性 图5显示了3D ResNets-34分类结果的示例。每行的帧都在中心位置裁剪,并显示部分原始视频。前三行是正确识别的结果。最下面一行是错误识别的结果。 图5 3D ResNets-34在Kinetics上的识别结果示例。 7. 结论 文章探索了具有...
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天手把手带你亲自复现1篇论文,掌握论文复现全流程。 以下是论文笔记部分: 2D CNN的卷积核参数较少,可以达到较深的深度。
项目:3D ResNets for Action Recognition 论文复现 本项目源于百度顶会论文复现营 课程链接 中的一篇论文复现。 背景介绍(详见课程内容 课程链接) 自己复现时最主要的代码 自己复现结果 备注: 可进一步的尝试 具体实现过程 问题: 进程被Killed ,有时会提示 “ 内存溢出,请检查相关程序 ” 1. 解压数据集 2. 视频...
3D ResNets for Action Recognition Update (2020/4/13) We published a paper on arXiv. Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh, "Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs", arXiv preprint, arXiv:2004.04968, 2020. We uploaded the pretrained mode...
3D ResNets for Action Recognition This is the PyTorch code for the following papers: Kensho Hara, Hirokatsu Kataoka, and Yutaka Satoh, "Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?", arXiv preprint, arXiv:1711.09577, 2017. ...
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...
Action recognition is one of the important computer vision tasks, which has many applications. This paper proposes a Multi-cue based Four-stream 3D ResNets (MF3D) model for action recognition. The proposed MF3D model contains four streams: a video saliency stream, an appearance stream, a ...
【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...
【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... ...
Learning Spatio-Temporal Features with 3D Residual Networksfor Action Recognition 代码地址: github: kenshohara/3D-ResNets-PyTorch 其他可参考代码: github: MRzzm/action-recognition-models-pytorch PaddlePaddle:github.com/PaddlePaddle 论文及课程体会 最大的感受是,通过学习,体会到了如何讨论科研问题和改进模型结...