DeepFace: Closing the Gap to Human-Level Performance in Face Verification
這篇文章是Facebook公司發表於CVPR2014的Oral文章, 這段時間非常火，一衆科技媒體都在熱炒「計算機的人臉識別能力正在趕超人類或者已經趕超了人類」，甚至微博上有人斷言，CV研究的最高境界就是「用最牛的機器，實現最深度的算法」。鋪墊到此爲止，我們進入正題，由我的視角帶領大家讀一讀這篇火的一談糊塗的文章。 0. 本文的貢獻 DeepFace一文依舊是沿着「檢測-對齊-人臉表示-
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- 1. [人臉識別]DeepFace: Closing the Gap to Human-Level Performance in Face Verification論文綜述(2015)
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- 8. Learning a Similarity Metric Discriminatively, with Application to Face Verification
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相關文章
- 1. [人臉識別]DeepFace: Closing the Gap to Human-Level Performance in Face Verification論文綜述(2015)
- 2. 【論文整理】DNN-Face-Recognition-Papers DeepFace
- 3. deepface
- 4. DeepFace筆記
- 5. 【DeepFace】人臉識別模型之DeepFace框架
- 6. Learning to Detect Fake Face Images in the Wild
- 7. 【論文整理】Face Related Papers and Code Collection Image-based Template Genearator
- 8. Learning a Similarity Metric Discriminatively, with Application to Face Verification
- 9. Learning a Similarity Metric Discriminatively, with Application to Face Verification.
- 10. PBS: Extract More Information from Datasets to Improve the Performance of Face Detection