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Title | REALY: Rethinking the Evaluation of 3D Face |
Description | REALY: Rethinking the Evaluation of 3D Face Reconstruction ECCV 2022 Zenghao Chai*, Haoxian Zhang*, Jing Ren, Di Kang, Zhengzhuo Xu, Xuefei Zhe, Chun Yuan |
Keywords | N/A |
WebSite | realy3dface.com |
Host IP | 185.199.111.153 |
Location | - |
Site | Rank |
US$1,227,439
Last updated: 2022-12-20 20:20:55
realy3dface.com has Semrush global rank of 8,623,080. realy3dface.com has an estimated worth of US$ 1,227,439, based on its estimated Ads revenue. realy3dface.com receives approximately 141,628 unique visitors each day. Its web server is located in -, with IP address 185.199.111.153. According to SiteAdvisor, realy3dface.com is safe to visit. |
Purchase/Sale Value | US$1,227,439 |
Daily Ads Revenue | US$1,134 |
Monthly Ads Revenue | US$33,991 |
Yearly Ads Revenue | US$407,888 |
Daily Unique Visitors | 9,442 |
Note: All traffic and earnings values are estimates. |
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realy3dface.com. | A | 598 | IP: czh-98.github.io. |
czh-98.github.io. | A | 3597 | IP: 185.199.111.153 |
czh-98.github.io. | A | 3597 | IP: 185.199.110.153 |
czh-98.github.io. | A | 3597 | IP: 185.199.109.153 |
czh-98.github.io. | A | 3597 | IP: 185.199.108.153 |
realy3dface.com. | AAAA | 597 | IPV6: czh-98.github.io. |
czh-98.github.io. | AAAA | 3600 | IPV6: 2606:50c0:8000::153 |
czh-98.github.io. | AAAA | 3600 | IPV6: 2606:50c0:8001::153 |
czh-98.github.io. | AAAA | 3600 | IPV6: 2606:50c0:8002::153 |
czh-98.github.io. | AAAA | 3600 | IPV6: 2606:50c0:8003::153 |
realy3dface.com. | NS | 597 | NS Record: czh-98.github.io. |
realy3dface.com. | MX | 597 | MX Record: czh-98.github.io. |
realy3dface.com. | TXT | 598 | TXT Record: czh-98.github.io. |
REALY: Rethinking the Evaluation of 3D Face Reconstruction ECCV 2022 Zenghao Chai*, Haoxian Zhang*, Jing Ren, Di Kang, Zhengzhuo Xu, Xuefei Zhe, Chun Yuan † , Linchao Bao † (* Equal Contribution, † Corresponding Author) Paper Supplementary Code Abstract The evaluation of 3D face reconstruction results typically relies on a rigid shape alignment between the estimated 3D model and the ground-truth scan. We observe that aligning two shapes with different reference points can largely affect the evaluation results. This poses difficulties for precisely diagnosing and improving a 3D face reconstruction method. In this paper, we propose a novel evaluation approach with a new benchmark REALY, consists of 100 globally aligned face scans with accurate facial keypoints, high-quality region masks, and topology-consistent meshes. Our approach performs region-wise shape alignment and leads to more accurate, bidirectional correspondences during computing the shape errors. The fine-grained, |
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