mlsanityData to 14 Oct 2026

PAtt-Lite: Lightweight Patch and Attention MobileNet for Challenging Facial Expression Recognition

arXiv 2306.09626 ↗First posted 16 Jun 2023cs.CVcited by 7

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Abstract (arXiv)

Facial Expression Recognition (FER) is a machine learning problem that deals with recognizing human facial expressions. While existing work has achieved performance improvements in recent years, FER in the wild and under challenging conditions remains a challenge. In this paper, a lightweight patch and attention network based on MobileNetV1, referred to as PAtt-Lite, is proposed to improve FER performance under challenging conditions. A truncated ImageNet-pre-trained MobileNetV1 is utilized as the backbone feature extractor of the proposed method. In place of the truncated layers is a patch extraction block that is proposed for extracting significant local facial features to enhance the representation from MobileNetV1, especially under challenging conditions. An attention classifier is also proposed to improve the learning of these patched feature maps from the extremely lightweight feature extractor. The experimental results on public benchmark databases proved the effectiveness of the proposed method. PAtt-Lite achieved state-of-the-art results on CK+, RAF-DB, FER2013, FERPlus, and the challenging conditions subsets for RAF-DB and FERPlus.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 40 of its 62 references that are in the map. First posted on arXiv 16 Jun 2023.

Builds on

40 of 62 references.

References · 40

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28 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 3; 2026: 1.

7 papers.

  1. 2024Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuningcited by 121
  2. 2026Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understandingcited by 5
  3. 2024MultiMAE-DER: Multimodal Masked Autoencoder for Dynamic Emotion Recognitioncited by 3
  4. 2024MTCAE-DFER: Multi-Task Cascaded Autoencoder for Dynamic Facial Expression Recognitioncited by 1
  5. 2025A Visual Self-attention Mechanism Facial Expression Recognition Network beyond Convnextcited by 0
  6. 2025Facial Emotion Recognition does not detect feeling unsafe in automated drivingcited by 0
  7. 2025MotivNet: Evolving Meta-Sapiens into an Emotionally Intelligent Foundation Modelcited by 0