{"action":"created","issue":{"url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/5","repository_url":"https://api.github.com/repos/zengarden/light_head_rcnn","labels_url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/5/comments","events_url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/5/events","html_url":"https://github.com/zengarden/light_head_rcnn/issues/5","id":313560382,"number":5,"title":"Does the rpn and the rcnn trained dividly?","user":{"login":"hasuoshenyun","id":16149291,"avatar_url":"https://avatars0.githubusercontent.com/u/16149291?v=4","gravatar_id":"","url":"https://api.github.com/users/hasuoshenyun","html_url":"https://github.com/hasuoshenyun","followers_url":"https://api.github.com/users/hasuoshenyun/followers","following_url":"https://api.github.com/users/hasuoshenyun/following{/other_user}","gists_url":"https://api.github.com/users/hasuoshenyun/gists{/gist_id}","starred_url":"https://api.github.com/users/hasuoshenyun/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hasuoshenyun/subscriptions","organizations_url":"https://api.github.com/users/hasuoshenyun/orgs","repos_url":"https://api.github.com/users/hasuoshenyun/repos","events_url":"https://api.github.com/users/hasuoshenyun/events{/privacy}","received_events_url":"https://api.github.com/users/hasuoshenyun/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-04-12T03:04:07Z","updated_at":"2018-04-14T14:27:25Z","closed_at":"2018-04-13T01:21:51Z","author_association":"NONE","body":"In the faster rcnn work, the writer said :\r\nIn the first step, we train the RPN as described above. This network is initialized with an ImageNet-\r\npre-trained model and fine-tuned end-to-end for the region proposal task. In the second step, we\r\ntrain a separate detection network by Fast R-CNN using the proposals generated by the step-1 RPN.\r\nThis detection network is also initialized by the ImageNet-pre-trained model. At this point the two\r\nnetworks do not share conv layers. In the third step, we use the detector network to initialize RPN\r\ntraining, but we fix the shared conv layers and only fine-tune the layers unique to RPN. Now the two\r\nnetworks share conv layers. Finally, keeping the shared conv layers fixed, we fine-tune the fc layers\r\nof the Fast R-CNN. As such, both networks share the same conv layers and form a unified network.\r\nBut I didn't find this step in your code? Could you please explain it"},"comment":{"url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/comments/381332901","html_url":"https://github.com/zengarden/light_head_rcnn/issues/5#issuecomment-381332901","issue_url":"https://api.github.com/repos/zengarden/light_head_rcnn/issues/5","id":381332901,"user":{"login":"Devin147","id":33034958,"avatar_url":"https://avatars3.githubusercontent.com/u/33034958?v=4","gravatar_id":"","url":"https://api.github.com/users/Devin147","html_url":"https://github.com/Devin147","followers_url":"https://api.github.com/users/Devin147/followers","following_url":"https://api.github.com/users/Devin147/following{/other_user}","gists_url":"https://api.github.com/users/Devin147/gists{/gist_id}","starred_url":"https://api.github.com/users/Devin147/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Devin147/subscriptions","organizations_url":"https://api.github.com/users/Devin147/orgs","repos_url":"https://api.github.com/users/Devin147/repos","events_url":"https://api.github.com/users/Devin147/events{/privacy}","received_events_url":"https://api.github.com/users/Devin147/received_events","type":"User","site_admin":false},"created_at":"2018-04-14T14:27:25Z","updated_at":"2018-04-14T14:27:25Z","author_association":"NONE","body":"@zengarden  Jointly train RPN and R-CNN? Do you mean that you adopt the third training strategy mentioned in Faster R-CNN because of ROI Align？"}}
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