{"action":"created","issue":{"url":"https://api.github.com/repos/wy1iu/sphereface/issues/19","repository_url":"https://api.github.com/repos/wy1iu/sphereface","labels_url":"https://api.github.com/repos/wy1iu/sphereface/issues/19/labels{/name}","comments_url":"https://api.github.com/repos/wy1iu/sphereface/issues/19/comments","events_url":"https://api.github.com/repos/wy1iu/sphereface/issues/19/events","html_url":"https://github.com/wy1iu/sphereface/issues/19","id":251182232,"number":19,"title":"Mirroring and Multi-patch approach","user":{"login":"commanderka","id":25139182,"avatar_url":"https://avatars0.githubusercontent.com/u/25139182?v=4","gravatar_id":"","url":"https://api.github.com/users/commanderka","html_url":"https://github.com/commanderka","followers_url":"https://api.github.com/users/commanderka/followers","following_url":"https://api.github.com/users/commanderka/following{/other_user}","gists_url":"https://api.github.com/users/commanderka/gists{/gist_id}","starred_url":"https://api.github.com/users/commanderka/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/commanderka/subscriptions","organizations_url":"https://api.github.com/users/commanderka/orgs","repos_url":"https://api.github.com/users/commanderka/repos","events_url":"https://api.github.com/users/commanderka/events{/privacy}","received_events_url":"https://api.github.com/users/commanderka/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2017-08-18T08:57:48Z","updated_at":"2017-08-28T09:27:56Z","closed_at":null,"body":"Hi,\r\n\r\nin the figures of your papers you can see that the 3-patch net outperforms the one patch net and you say that the 3-patch feature vector is formed by concatenating the feature vectors of each patch. However, you do not say in your paper how these patches are computed. Do you use a different alignment strategy and train a new net on each type of aligned images or do you introduce a small offset and extract the 3-patch features by just transforming the original image a bit and computing the features with the original net?\r\nFurthermore I get better results when not concatenating the features of the mirrored image. Has anyone experimented on that (patch selection/(not) mirroring) ? "},"comment":{"url":"https://api.github.com/repos/wy1iu/sphereface/issues/comments/325306269","html_url":"https://github.com/wy1iu/sphereface/issues/19#issuecomment-325306269","issue_url":"https://api.github.com/repos/wy1iu/sphereface/issues/19","id":325306269,"user":{"login":"CasiaFan","id":10608984,"avatar_url":"https://avatars3.githubusercontent.com/u/10608984?v=4","gravatar_id":"","url":"https://api.github.com/users/CasiaFan","html_url":"https://github.com/CasiaFan","followers_url":"https://api.github.com/users/CasiaFan/followers","following_url":"https://api.github.com/users/CasiaFan/following{/other_user}","gists_url":"https://api.github.com/users/CasiaFan/gists{/gist_id}","starred_url":"https://api.github.com/users/CasiaFan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/CasiaFan/subscriptions","organizations_url":"https://api.github.com/users/CasiaFan/orgs","repos_url":"https://api.github.com/users/CasiaFan/repos","events_url":"https://api.github.com/users/CasiaFan/events{/privacy}","received_events_url":"https://api.github.com/users/CasiaFan/received_events","type":"User","site_admin":false},"created_at":"2017-08-28T09:27:56Z","updated_at":"2017-08-28T09:27:56Z","body":"@wy1iu Thanks for you response! But how do you choose the patches? Crop patches from aligned face region centered at some particular landmarks then resize to 96x112 before inputting to networks? Or just randomly crop with given size from initial face region?"}}
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