【论文阅读笔记】Large-scale Video Classification with Convolutional Neural Networks
论文贡献： 1.采用多种方法扩展CNN到视频识别，并用Sports-1M数据集进行验证和测试。 2.提出了将输入处理为低分辨率流和高分辨率流的方法，在不影响精确度的前提下显著减少了CNN的训练时间。 3.验证模型能够扩展到UCF101数据集上，且显著提升了精确率。 时间信息融合模型： a）单帧模型（Single-frame）：用于得到静态图像对视频分类的贡献。CNN结构：C(96,11,3)-N-
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