【論文閱讀筆記】Large-scale Video Classification with Convolutional Neural Networks
論文貢獻： 1.採用多種方法擴展CNN到視頻識別，並用Sports-1M數據集進行驗證和測試。 2.提出了將輸入處理爲低分辨率流和高分辨率流的方法，在不影響精確度的前提下顯著減少了CNN的訓練時間。 3.驗證模型能夠擴展到UCF101數據集上，且顯著提升了精確率。 時間信息融合模型： a）單幀模型（Single-frame）：用於得到靜態圖像對視頻分類的貢獻。CNN結構：C(96,11,3)-N-
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