Face Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

25 leaderboard tables shown for this task, 25 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 25 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

67 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 67 until expanded.

Subtasks archive 2025-07-28

6 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 639 papers with code (2,329 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• FaceNet: A Unified Embedding for Face Recognition and Clustering
  12 Mar 2015 183 repositories listed Syntology ran 65 of 154 samples · 89 unverified · 45 pointer-only (licence)
  On the widely used Labeled Faces in the Wild (LFW) dataset, our system achieves a new record accuracy of 99.
• ArcFace: Additive Angular Margin Loss for Deep Face Recognition
  23 Jan 2018 100 repositories listed Syntology ran 16 of 21 samples · 5 unverified · 14 pointer-only (licence)
  Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability.
• VGGFace2: A dataset for recognising faces across pose and age
  23 Oct 2017 24 repositories listed Syntology ran 5 of 8 samples · 3 unverified · 5 pointer-only (licence)
  The dataset was collected with three goals in mind: (i) to have both a large number of identities and also a large number of images for each identity; (ii) to cover a large range of pose, age and ethnicity; and (iii) to…
• SphereFace: Deep Hypersphere Embedding for Face Recognition
  26 Apr 2017 22 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)
  This paper addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably…
• A Light CNN for Deep Face Representation with Noisy Labels
  9 Nov 2015 19 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  This paper presents a Light CNN framework to learn a compact embedding on the large-scale face data with massive noisy labels.
• Circle Loss: A Unified Perspective of Pair Similarity Optimization
  25 Feb 2020 16 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity sₚ and minimize the between-class similarity sₙ.
• Learning Face Representation from Scratch
  28 Nov 2014 15 repositories listed Syntology ran 1 of 11 samples · 10 unverified
  The current situation in the field of face recognition is that data is more important than algorithm.
• MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
  27 Jul 2016 12 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In this paper, we design a benchmark task and provide the associated datasets for recognizing face images and link them to corresponding entity keys in a knowledge base.
• CosFace: Large Margin Cosine Loss for Deep Face Recognition
  29 Jan 2018 11 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  The central task of face recognition, including face verification and identification, involves face feature discrimination.
• RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
  5 May 2021 10 repositories listed Syntology ran 2 of 14 samples · 12 unverified
  We propose RepMLP, a multi-layer-perceptron-style neural network building block for image recognition, which is composed of a series of fully-connected (FC) layers.
• AdaFace: Quality Adaptive Margin for Face Recognition
  3 Apr 2022 9 repositories listed Syntology ran 17 of 22 samples · 5 unverified · 11 pointer-only (licence)
  In this work, we introduce another aspect of adaptiveness in the loss function, namely the image quality.
• Can we still avoid automatic face detection?
  14 Feb 2016 9 repositories listed
  In this setting, is it still possible for privacy-conscientious users to avoid automatic face detection and recognition?
• DeepID3: Face Recognition with Very Deep Neural Networks
  3 Feb 2015 9 repositories listed
  Very deep neural networks recently achieved great success on general object recognition because of their superb learning capacity.
• Learning Meta Face Recognition in Unseen Domains
  17 Mar 2020 8 repositories listed
  Face recognition systems are usually faced with unseen domains in real-world applications and show unsatisfactory performance due to their poor generalization.
• Deep Face Recognition: A Survey
  18 Apr 2018 8 repositories listed
  Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction.
• GhostFaceNets: Lightweight Face Recognition Model From Cheap Operations
  10 Apr 2023 7 repositories listed
  The development of deep learning-based biometric models that can be deployed on devices with constrained memory and computational resources has proven to be a significant challenge.
• Partial FC: Training 10 Million Identities on a Single Machine
  11 Oct 2020 7 repositories listed
  The experiment demonstrates no loss of accuracy when training with only 10\% randomly sampled classes for the softmax-based loss functions, compared with training with full classes using state-of-the-art models on…
• Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
  9 Jul 2019 7 repositories listed
  The proposed approach achieves an HTER of 0% in Replay Mobile dataset and an ACER of 0.
• FaceQnet: Quality Assessment for Face Recognition based on Deep Learning
  3 Apr 2019 7 repositories listed
  Several conclusions can be drawn from this work, most notably: 1) we managed to employ an existing ICAO compliance framework and a pretrained CNN to automatically label data with quality information, 2) we trained…
• Compact Bilinear Pooling
  19 Nov 2015 7 repositories listed
  Bilinear models has been shown to achieve impressive performance on a wide range of visual tasks, such as semantic segmentation, fine grained recognition and face recognition.
• SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
  24 May 2022 6 repositories listed
  Deep face recognition has achieved great success due to large-scale training databases and rapidly developing loss functions.
• Killing Two Birds with One Stone:Efficient and Robust Training of Face Recognition CNNs by Partial FC
  28 Mar 2022 6 repositories listed Syntology ran 4 of 12 samples · 8 unverified · 4 pointer-only (licence)
  In each iteration, positive class centers and a random subset of negative class centers are selected to compute the margin-based softmax loss.
• Masked Face Recognition for Secure Authentication
  25 Aug 2020 6 repositories listed Syntology ran 1 of 12 samples · 11 unverified
  The use of these face masks has raised a serious question on the accuracy of the facial recognition system used for tracking school/office attendance and to unlock phones.
• SeesawFaceNets: sparse and robust face verification model for mobile platform
  24 Aug 2019 6 repositories listed Syntology ran 7 of 17 samples · 10 unverified · 5 pointer-only (licence)
  Therefore, designing lightweight networks with low memory requirement and computational cost is one of the most practical solutions for face verification on mobile platform.
• AdaCos: Adaptively Scaling Cosine Logits for Effectively Learning Deep Face Representations
  1 May 2019 6 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  Our results show that training deep neural networks with the AdaCos loss is stable and able to achieve high face recognition accuracy.
• Deep Polynomial Neural Networks
  20 Jun 2020 5 repositories listed
  We introduce three tensor decompositions that significantly reduce the number of parameters and show how they can be efficiently implemented by hierarchical neural networks.
• SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
  20 Mar 2020 5 repositories listed
  Face image quality is an important factor to enable high performance face recognition systems.
• Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
  18 Mar 2020 5 repositories listed
  Depth supervised learning has been proven as one of the most effective methods for face anti-spoofing.
• Searching Central Difference Convolutional Networks for Face Anti-Spoofing
  9 Mar 2020 5 repositories listed
  Here we propose a novel frame level FAS method based on Central Difference Convolution (CDC), which is able to capture intrinsic detailed patterns via aggregating both intensity and gradient information.
• Support Vector Guided Softmax Loss for Face Recognition
  29 Dec 2018 5 repositories listed
  Face recognition has witnessed significant progresses due to the advances of deep convolutional neural networks (CNNs), the central challenge of which, is feature discrimination.

Syntology lines on 15 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.