Ashish Patel 🇮🇳’s Post

𝗗𝗮𝘆-𝟭𝟲𝟭 Computer Vision Learning 𝗔𝗖𝗡𝗲: Attentive Context Normalization for Robust Permutation-Equivariant Learning by Google Research and University of Victoria Follow me for similar post:  🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in CVPR 2020 with over 22 citations. 🔸 It Outperforms with the RANSAC, CNe, PointNet, etc. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/eA8SmfA code : https://lnkd.in/eyhNWx7 ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸Many problems in computer vision require dealing with sparse, unstructured data in the form of point clouds. Permutation-equivariant networks have become a popular solution – they operate on individual data points with simple perceptrons and extract contextual information with global pooling strategies. 🔸 Attentive Context Normalization (ACN), a simple yet effective technique to build permutation-equivariant networks robust to outliers. Specifically, we show how to normalize the feature maps with weights that are estimated within the network so that outliers are excluded from the normalization.  #computervision #artificialintelligence #innovation