mlsanityData to 14 Oct 2026

Face Pyramid Vision Transformer

arXiv 2210.11974 ↗First posted 21 Oct 2022cs.CVcited by 5

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Abstract (arXiv)

A novel Face Pyramid Vision Transformer (FPVT) is proposed to learn a discriminative multi-scale facial representations for face recognition and verification. In FPVT, Face Spatial Reduction Attention (FSRA) and Dimensionality Reduction (FDR) layers are employed to make the feature maps compact, thus reducing the computations. An Improved Patch Embedding (IPE) algorithm is proposed to exploit the benefits of CNNs in ViTs (e.g., shared weights, local context, and receptive fields) to model lower-level edges to higher-level semantic primitives. Within FPVT framework, a Convolutional Feed-Forward Network (CFFN) is proposed that extracts locality information to learn low level facial information. The proposed FPVT is evaluated on seven benchmark datasets and compared with ten existing state-of-the-art methods, including CNNs, pure ViTs, and Convolutional ViTs. Despite fewer parameters, FPVT has demonstrated excellent performance over the compared methods. Project page is available at https://khawar-islam.github.io/fpvt/

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 27 of its 40 references that are in the map. First posted on arXiv 21 Oct 2022.

Builds on

27 of 40 references.

References · 27

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  4. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  5. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
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  11. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,962
  12. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,101
15 more
  1. 2021CvT: Introducing Convolutions to Vision Transformerscited by 947
  2. 2017VGGFace2: A dataset for recognising faces across pose and agecited by 914
  3. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  4. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  5. 2021Going deeper with Image Transformerscited by 764
  6. 2022Exploring Plain Vision Transformer Backbones for Object Detectioncited by 724
  7. 2021Rethinking Spatial Dimensions of Vision Transformerscited by 361
  8. 2021DeepViT: Towards Deeper Vision Transformercited by 289
  9. 2017Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environmentscited by 260
  10. 2021Incorporating Convolution Designs into Visual Transformerscited by 248
  11. 2021WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognitioncited by 223
  12. 2021P2T: Pyramid Pooling Transformer for Scene Understandingcited by 84
  13. 2021Face Transformer for Recognitioncited by 46
  14. 2021An Efficient Training Approach for Very Large Scale Face Recognitioncited by 12
  15. 2020Framework for Passenger Seat Availability Using Face Detection in Passenger Buscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 3.

5 papers.

  1. 2024GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editingcited by 14
  2. 2024Model Inversion Attacks Through Target-Specific Conditional Diffusion Modelscited by 8
  3. 2026ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptationcited by 0
  4. 2026Vision Transformers for Face Recognition Need More Registerscited by 0
  5. 2026A Step Forward Towards Trustworthy Risk-Aware Facial Retrieval (RA-FR)cited by 0