Ashish Patel 🇮🇳’s Post

𝗗𝗮𝘆-𝟭𝟱𝟯 Computer Vision Learning 𝗥𝗢𝗔𝗠: Recurrently Optimizing Tracking Model by City University of Hong Kong Follow me for a similar post:  🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in CVPR 2020 with over 26 citations. 🔸 It Outperforms MDNet, CF2, ECO, CCOT, GOTURN, SiamFC, SiamFCv2, etc. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/gGHgFzm ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 The article proposes that the model ROAM uses the method of generating heatmap response and border regression on the tracking target to track the target: 1. Use the adjustable size convolution filter to adapt to the shape change of the object, and the model does not need to design anchor points. 2. Using offline training recursive neural optimizer, meta-learning update tracking model method, so that the model can quickly converge. #computervision #artificialintelligence #innovation