{"id":20821375,"url":"https://github.com/richzhang/splitbrainauto","last_synced_at":"2025-05-07T16:23:53.769Z","repository":{"id":112517664,"uuid":"74920523","full_name":"richzhang/splitbrainauto","owner":"richzhang","description":"Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.","archived":false,"fork":false,"pushed_at":"2018-06-25T22:43:53.000Z","size":11390,"stargazers_count":138,"open_issues_count":3,"forks_count":31,"subscribers_count":10,"default_branch":"master","last_synced_at":"2024-07-05T14:13:25.312Z","etag":null,"topics":["autoencoder","caffe","unsupervised-learning"],"latest_commit_sha":null,"homepage":"http://richzhang.github.io/splitbrainauto","language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/richzhang.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-11-27T23:22:13.000Z","updated_at":"2024-03-29T22:44:09.000Z","dependencies_parsed_at":"2023-05-04T13:47:26.989Z","dependency_job_id":null,"html_url":"https://github.com/richzhang/splitbrainauto","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richzhang%2Fsplitbrainauto","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richzhang%2Fsplitbrainauto/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richzhang%2Fsplitbrainauto/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/richzhang%2Fsplitbrainauto/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/richzhang","download_url":"https://codeload.github.com/richzhang/splitbrainauto/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225096692,"owners_count":17420293,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["autoencoder","caffe","unsupervised-learning"],"created_at":"2024-11-17T22:12:04.048Z","updated_at":"2024-11-17T22:12:04.606Z","avatar_url":"https://github.com/richzhang.png","language":"Shell","readme":"## Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction [[Project Page]](http://richzhang.github.io/splitbrainauto/) ##\n[Richard Zhang](https://richzhang.github.io/), [Phillip Isola](http://web.mit.edu/phillipi/), [Alexei A. Efros](http://www.eecs.berkeley.edu/~efros/). In CVPR, 2017. (hosted on [ArXiv](https://arxiv.org/abs/1611.09842))\n\n\u003cimg src=\"http://richzhang.github.io/index_files/cvpr2017_splitbrain.png\" height=\"180\" /\u003e\n\n### Overview ###\nThis repository contains a pre-trained Split-Brain Autoencoder network. The network achieves state-of-the-art results on several large-scale unsupervised representation learning benchmarks.\n\n### Clone this repository ###\nClone the master branch of the respository using `git clone -b master --single-branch https://github.com/richzhang/splitbrainauto.git`\n\n### Dependencies ###\nThis code requires a working installation of [Caffe](http://caffe.berkeleyvision.org/). For guidelines and help with installation of Caffe, consult the [installation guide](http://caffe.berkeleyvision.org/) and [Caffe users group](https://groups.google.com/forum/#!forum/caffe-users).\n\n### Test-Time Usage ###\n**(1)** Run `./resources/fetch_models.sh`. This will load model `model_splitbrainauto_clcl.caffemodel`. It will also load model `model_splitbrainauto_clcl_rs.caffemodel`, which is the model with the rescaling method from [Kr\u0026auml;henb\u0026uuml;hl et al. ICLR 2016](https://github.com/philkr/magic_init) applied. The rescaling method has been shown to improve fine-tuning performance in some models, and we use it for the PASCAL tests in Table 4 in the paper. Alternatively, download the models from [here](https://people.eecs.berkeley.edu/~rich.zhang/projects/2017_splitbrain/files/models/) and put them in the `models` directory.\n\n**(2)** To extract features, you can (a) use the main branch of Caffe and do color conversion outside of the network or (b) download and install a modified Caffe and not worry about color conversion.\n\n**(a)** **Color conversion outside of prototxt** To extract features with the main branch of [Caffe](http://caffe.berkeleyvision.org/): \u003cbr\u003e\n**(i)** Load the downloaded weights with model definition file `deploy_lab.prototxt` in the `models` directory. The input is blob `data_lab`, which is an ***image in Lab colorspace***. You will have to do the Lab color conversion pre-processing outside of the network.\n\n**(b)** **Color conversion in prototxt** You can also extract features with in-prototxt color version with a modified Caffe. \u003cbr\u003e\n**(i)** Run `./resources/fetch_caffe.sh`. This will load a modified Caffe into directory `./caffe-colorization`. \u003cbr\u003e\n**(ii)** Install the modified Caffe. For guidelines and help with installation of Caffe, consult the [installation guide](http://caffe.berkeleyvision.org/) and [Caffe users group](https://groups.google.com/forum/#!forum/caffe-users). \u003cbr\u003e\n**(iii)** Load the downloaded weights with model definition file `deploy.prototxt` in the `models` directory. The input is blob `data`, which is a ***non mean-centered BGR image***.\n\n### Citation ###\nIf you find this model useful for your resesarch, please use this [bibtex](http://richzhang.github.io/index_files/bibtex_cvpr2017_splitbrain.txt) to cite.\n \n","funding_links":[],"categories":["Computer Vision"],"sub_categories":["Image Representation Learning"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frichzhang%2Fsplitbrainauto","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frichzhang%2Fsplitbrainauto","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frichzhang%2Fsplitbrainauto/lists"}