{"id":18614498,"url":"https://github.com/wbjang/code-nerf","last_synced_at":"2025-04-11T00:30:48.986Z","repository":{"id":37480302,"uuid":"396326343","full_name":"wbjang/code-nerf","owner":"wbjang","description":"Official repository for CodeNeRF","archived":false,"fork":false,"pushed_at":"2024-02-21T16:29:27.000Z","size":37,"stargazers_count":126,"open_issues_count":5,"forks_count":15,"subscribers_count":16,"default_branch":"main","last_synced_at":"2024-11-07T03:31:47.662Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","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/wbjang.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-08-15T11:19:05.000Z","updated_at":"2024-10-24T08:29:47.000Z","dependencies_parsed_at":"2024-11-07T03:40:36.254Z","dependency_job_id":null,"html_url":"https://github.com/wbjang/code-nerf","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/wbjang%2Fcode-nerf","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wbjang%2Fcode-nerf/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wbjang%2Fcode-nerf/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wbjang%2Fcode-nerf/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wbjang","download_url":"https://codeload.github.com/wbjang/code-nerf/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248322220,"owners_count":21084333,"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":[],"created_at":"2024-11-07T03:25:57.978Z","updated_at":"2025-04-11T00:30:46.446Z","avatar_url":"https://github.com/wbjang.png","language":"Python","funding_links":[],"categories":["Papers"],"sub_categories":["Unclassified"],"readme":"\n\n\n## CodeNeRF: Disentangled Neural Radiance Fields for Object Categories\n\nDate : 27th Feb, 2022\n\nThis contains the implementation of the paper [CodeNeRF](https://arxiv.org/abs/2109.01750). \nPlease refer to the [project webpage](https://sites.google.com/view/wbjang/home/codenerf) for demos.\n\n\n### Install the environment\n\n\n```\nconda env create -f environment.yml\nconda activate code_nerf\n```\n\n### Catalog\n\n- [x] Training\n- [x] Optimizing with GT pose\n- [ ] Editing Shapes/Textures\n- [ ] Pose Optimizing\n\n\n### Download the data (ShapeNet-SRN)\n\nFor ShapeNet-SRN dataset, you can download it from https://drive.google.com/drive/folders/1PsT3uKwqHHD2bEEHkIXB99AlIjtmrEiR\n\n### Training\n\n```\npython train.py --gpu \u003cgpu_id\u003e --save_dir \u003csave_dir\u003e --jsonfiles \u003cjsonfile.json\u003e --iters_crop 1000000 --iters_all 1200000\n```\n\nJSON files contain hyper-parameters as well as data directory. 'iters_crop' and 'iters_all' are number of iterations for both cropped and whole images.\n\n### Optimizing\n\n```\npython optimize.py --gpu \u003cgpu_id\u003e --saved_dir \u003ctrained_dir\u003e\n```\n\nThe result will be stored in \u003ctrained_dir/test(_num)\u003e, and each folder contains the progress of optimization, and the evaluation of test set. \nThe final optimized results and the quantitative evaluations are stored in 'trained_dir/test(_num)/codes.pth'\n\n\n\n\n### BibTex\n\n```\n@inproceedings{jang2021codenerf,\n  title={Codenerf: Disentangled neural radiance fields for object categories},\n  author={Jang, Wonbong and Agapito, Lourdes},\n  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},\n  pages={12949--12958},\n  year={2021}\n}\n```\n\n### References\n\nSome parts of code are borrowed from below amazing repositories.\n\n* The GitHub repository of Pixel NeRF : https://github.com/sxyu/pixel-nerf\n* nerf_pl : https://github.com/kwea123/nerf_pl\n* NeRF-pytorch : https://github.com/yenchenlin/nerf-pytorch\n\n\n### Supplementary Video\n\nhttps://user-images.githubusercontent.com/32883157/130004248-0ff74d4e-993e-43f2-91ee-bd25776e65bc.mp4\n\n\n### License\n\nMIT\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwbjang%2Fcode-nerf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwbjang%2Fcode-nerf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwbjang%2Fcode-nerf/lists"}