ð——ð—®ð˜†-ðŸðŸ¯ðŸ´ Computer Vision Learning ð—Ÿð—¼ð—™ð—§ð—¥: Detector-Free Local Feature Matching with Transformers by SenseTime Research and Zhejiang Univerisity Follow me for a similar post:  🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in CVPR 2021 with over 3 citations. 🔸 It Outperforms with D2Net, R2D2, DISK, SP + SuperGlue, etc. ------------------------------------------------------------------- ð—”ð—ºð—®ð˜‡ð—¶ð—»ð—´ ð—¥ð—²ð˜€ð—²ð—®ð—¿ð—°ð—µ : https://lnkd.in/eXkB_hr Code : https://lnkd.in/enG7TpT ------------------------------------------------------------------- ð—œð— ð—£ð—¢ð—¥ð—§ð—”ð—¡ð—–𗘠🔸 LoFTR is a novel method of feature matching. 🔸 Instead of matching the features matching sequentially this method used pixel-wise dense matches at the coarse level and later refine the good matches at a fine level.  #computervision #artificialintelligence #machinelearning
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For previous post visit this github : https://github.com/ashishpatel26/365-Days-Computer-Vision-Learning-Linkedin-Post