{"id":20256564,"url":"https://github.com/interdigitalinc/wrappingnet","last_synced_at":"2025-06-17T05:35:04.365Z","repository":{"id":246447584,"uuid":"815270535","full_name":"InterDigitalInc/WrappingNet","owner":"InterDigitalInc","description":"Implementation of the WrappingNet","archived":false,"fork":false,"pushed_at":"2024-06-28T00:20:57.000Z","size":738,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-01-14T03:44:58.107Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/InterDigitalInc.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":"2024-06-14T18:19:13.000Z","updated_at":"2024-10-18T17:40:14.000Z","dependencies_parsed_at":"2024-06-28T02:04:55.101Z","dependency_job_id":null,"html_url":"https://github.com/InterDigitalInc/WrappingNet","commit_stats":null,"previous_names":["interdigitalinc/wrappingnet"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InterDigitalInc%2FWrappingNet","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InterDigitalInc%2FWrappingNet/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InterDigitalInc%2FWrappingNet/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InterDigitalInc%2FWrappingNet/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/InterDigitalInc","download_url":"https://codeload.github.com/InterDigitalInc/WrappingNet/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241715023,"owners_count":20007913,"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":"2024-11-14T10:47:14.501Z","updated_at":"2025-03-03T17:56:10.233Z","avatar_url":"https://github.com/InterDigitalInc.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# WrappingNet\n\nImplementation of the WrappingNet architecture.\u003cbr\u003e\nThe entire framework is illustrated below.\n\n\u003cimg src=\"architecture.png\" alt=\"drawing\" width=\"720\"/\u003e\n\n## Data Preparation\nThe dataset for WrappingNet should be prepared as follows:\n### For training\n1. `mkdir -p datasets/Manifold40; cd datasets/Manifold40`\n2. Download processed.zip from `https://aspera.pub/3O5IeFo` then move into `datasets/Manifold40/`\n3. `unzip processed.zip`, then check the data under `datasets/Manifold40/processed/`\n### For evaluation\n4. `wget https://cg.cs.tsinghua.edu.cn/dataset/subdivnet/datasets/Manifold40.zip`\n5. `unzip Manifold40.zip`\n6. `mv Manifold40 raw` then check the data under `datasets/Manifold40/raw/`\n\n## Dependencies\n```\n   pytorch\n   pytorch-geometric\n   pytorch-lightning\n   pytorch-scatter\n   botorch\n   open3d\n   numpy\n```\n\n## To Run\nTo use our generalized face convolutions, follow these steps:\n1. Create a python environment with the above dependencies installed\n2. Go to `./nndistance/` and run `python build.py install`. This will build the faster chamfer distance module.\n3. Run `CUDA_VISIBLE_DEVICES={GPU}, bash scripts/LC.sh` or `CUDA_VISIBLE_DEVICES={GPU}, bash scripts/basesup3.sh` to launch a training script.\n\n## Citation\nEric Lei, Muhammad Asad Lodhi, Jiahao Pang, Junghyun Ahn, Dong Tian, \u003cbr\u003e\n\"*WrappingNet: Mesh Autoencoder via Deep Sphere Deformation*\", \u003cbr\u003e\nTo Appear in 2024 IEEE International Conference on Image Processing (ICIP).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finterdigitalinc%2Fwrappingnet","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finterdigitalinc%2Fwrappingnet","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finterdigitalinc%2Fwrappingnet/lists"}