關鍵字查詢 | 類別:會議論文 | | 關鍵字:Reptile Meta-Tracking

[第一頁][上頁]1[次頁][最末頁]目前在第 1 頁 / 共有 01 筆查詢結果
序號 學年期 教師動態
1 108/1 電機系 蔡奇謚 教授 會議論文 發佈 Reptile Meta-Tracking , [108-1] :Reptile Meta-Tracking會議論文Reptile Meta-TrackingShang-Jhih Jhang; Chi-Yi TsaiGeneric object tracking;visual tracking;deep learning;few-shot learning;Reptile meta-learningIEEEGeneric object tracking (GOT) is one of the main topics in computer vision for many years. The goal of GOT is to recognize and locate a specific object in the form of bounding box throughout a sequence of images. Moreover, GOT also requires algorithms to locate objects down to instances level. These requirements produce some unique challenges especially for deep learning based GOT algorithms that may easily become over-fitting if given a really small training dataset of the object during the online tracking process. To deal with this issue, we propose a novel Reptile meta-tracking algorithm, which adopts a first-order meta-learning technique so that during initialization, the visual tracker only requires few training examples and few steps of optimization to perform well. The proposed Reptile meta-tracker is evaluate
[第一頁][上頁]1[次頁][最末頁]目前在第 1 頁 / 共有 01 筆查詢結果