{"action":"opened","issue":{"url":"https://api.github.com/repos/cvlab-epfl/LIFT/issues/14","repository_url":"https://api.github.com/repos/cvlab-epfl/LIFT","labels_url":"https://api.github.com/repos/cvlab-epfl/LIFT/issues/14/labels{/name}","comments_url":"https://api.github.com/repos/cvlab-epfl/LIFT/issues/14/comments","events_url":"https://api.github.com/repos/cvlab-epfl/LIFT/issues/14/events","html_url":"https://github.com/cvlab-epfl/LIFT/issues/14","id":208594002,"number":14,"title":"Hard mining the Descriptor network","user":{"login":"13331151","id":7379466,"avatar_url":"https://avatars.githubusercontent.com/u/7379466?v=3","gravatar_id":"","url":"https://api.github.com/users/13331151","html_url":"https://github.com/13331151","followers_url":"https://api.github.com/users/13331151/followers","following_url":"https://api.github.com/users/13331151/following{/other_user}","gists_url":"https://api.github.com/users/13331151/gists{/gist_id}","starred_url":"https://api.github.com/users/13331151/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/13331151/subscriptions","organizations_url":"https://api.github.com/users/13331151/orgs","repos_url":"https://api.github.com/users/13331151/repos","events_url":"https://api.github.com/users/13331151/events{/privacy}","received_events_url":"https://api.github.com/users/13331151/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-02-18T00:42:02Z","updated_at":"2017-02-18T00:42:02Z","closed_at":null,"body":"I follow your advice of adding hard mining, and the performance of descriptor network work better than before but its still far worse compared to your released version. I wondering if there is anything I can pay attention to? Have you pre-trained the network before mining? And I extract patch with 6*sift_scale as radius for descriptor input, is it right? As for the mining rate, I double the mining rate every 5000 batches, so the mining rate become 1 at the 35000th iteration, is it the same as what you described in the paper?\r\nI really appreciate your help because I have spent so much time in this part. Faint.... "}}
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