# Island Loss for Learning Discriminative Features in Facial Expression Recognition

arXiv: https://arxiv.org/abs/1710.03144 · HTML: https://mlsanity.com/paper/1710.03144/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2017.

## Built on by (most cited first, 30 of 35)

- [Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition](https://mlsanity.com/paper/2104.00232/) (2021)
- [Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition](https://mlsanity.com/paper/2109.07270/) (2021)
- [Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition](https://mlsanity.com/paper/2104.05160/) (2021)
- [Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition](https://mlsanity.com/paper/2212.05463/) (2022)
- [Uncertainty-aware Label Distribution Learning for Facial Expression Recognition](https://mlsanity.com/paper/2209.10448/) (2022)
- [Learning to Amend Facial Expression Representation via De-albino and Affinity](https://mlsanity.com/paper/2103.10189/) (2021)
- [Learning Vision Transformer with Squeeze and Excitation for Facial Expression Recognition](https://mlsanity.com/paper/2107.03107/) (2021)
- [Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understanding](https://mlsanity.com/paper/2304.00058/) (2023)
- [Latent-OFER: Detect, Mask, and Reconstruct with Latent Vectors for Occluded Facial Expression Recognition](https://mlsanity.com/paper/2307.11404/) (2023)
- [Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition](https://mlsanity.com/paper/2106.03487/) (2021)
- [Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion](https://mlsanity.com/paper/2307.13463/) (2023)
- [Disentangling Identity and Pose for Facial Expression Recognition](https://mlsanity.com/paper/2208.08106/) (2022)
- [ARBEx: Attentive Feature Extraction with Reliability Balancing for Robust Facial Expression Learning](https://mlsanity.com/paper/2305.01486/) (2023)
- [FER-former: Multi-modal Transformer for Facial Expression Recognition](https://mlsanity.com/paper/2303.12997/) (2023)
- [Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey](https://mlsanity.com/paper/2412.17616/) (2024)
- [Neuron with Steady Response Leads to Better Generalization](https://mlsanity.com/paper/2111.15414/) (2021)
- [Unsupervised Facial Expression Representation Learning with Contrastive Local Warping](https://mlsanity.com/paper/2303.09034/) (2023)
- [Rethinking Class Imbalance in Machine Learning](https://mlsanity.com/paper/2305.03900/) (2023)
- [Do Neural Network Weights account for Classes Centers?](https://mlsanity.com/paper/2104.07004/) (2021)
- [Dynamic Adaptive Threshold based Learning for Noisy Annotations Robust Facial Expression Recognition](https://mlsanity.com/paper/2208.10221/) (2022)
- [Adaptive Temporal Motion Guided Graph Convolution Network for Micro-expression Recognition](https://mlsanity.com/paper/2406.08997/) (2024)
- [A Deep Positive-Negative Prototype Approach to Integrated Prototypical Discriminative Learning](https://mlsanity.com/paper/2501.02477/) (2025)
- [Exp-Graph: How Connections Learn Facial Attributes in Graph-based Expression Recognition](https://mlsanity.com/paper/2507.14608/) (2025)
- [Landmark-Aware and Part-based Ensemble Transfer Learning Network for Facial Expression Recognition from Static images](https://mlsanity.com/paper/2104.11274/) (2021)
- [MixCut:A Data Augmentation Method for Facial Expression Recognition](https://mlsanity.com/paper/2405.10489/) (2024)
- [Multi-threshold Deep Metric Learning for Facial Expression Recognition](https://mlsanity.com/paper/2406.16434/) (2024)
- [Semantic Data Augmentation for Long-tailed Facial Expression Recognition](https://mlsanity.com/paper/2411.17254/) (2024)
- [Uncertainty-Aware Label Refinement on Hypergraphs for Personalized Federated Facial Expression Recognition](https://mlsanity.com/paper/2501.01816/) (2025)
- [An optimized Capsule-LSTM model for facial expression recognition with video sequences](https://mlsanity.com/paper/2106.07564/) (2021)
- [InFER: A Multi-Ethnic Indian Facial Expression Recognition Dataset](https://mlsanity.com/paper/2310.00287/) (2023)

## Abstract (arXiv)

Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on facial expression recognition. However, the performance degrades dramatically under real-world settings due to variations introduced by subtle facial appearance changes, head pose variations, illumination changes, and occlusions. In this paper, a novel island loss is proposed to enhance the discriminative power of the deeply learned features. Specifically, the IL is designed to reduce the intra-class variations while enlarging the inter-class differences simultaneously. Experimental results on four benchmark expression databases have demonstrated that the CNN with the proposed island loss (IL-CNN) outperforms the baseline CNN models with either traditional softmax loss or the center loss and achieves comparable or better performance compared with the state-of-the-art methods for facial expression recognition.