Awesome Face Recognition
A curated collection of academic papers covering all aspects of face analysis, including detection, recognition, alignment, generation, and anti-spoofing.
What is Awesome Face Recognition?
awesome-Face_Recognition is a curated GitHub repository that collects and categorizes academic research papers on face analysis. It covers a wide spectrum of topics including face detection, alignment, recognition, reconstruction, generation, transfer, anti-spoofing, and retrieval. The project solves the problem of fragmented information by providing a single, organized source for researchers to explore the state-of-the-art in face-related computer vision.
Computer vision researchers, PhD students, and engineers specializing in face analysis who need a comprehensive reference for literature review, benchmarking, and tracking advancements in the field.
Unlike generic paper lists, it offers deep, structured coverage of the face analysis domain with thematic categorization, code links, and integration of multiple community sources, saving significant time in literature survey and research planning.
Overview
papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;
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