AffectNet

Overview edit

Variants: AffectNet

Associated Benchmarks

This dataset is used in 3 benchmarks:

• Facial Expression Recognition (FER) - Metrics: Accuracy (8 emotion), Accuracy (7 emotion)
• Continuous Affect Estimation - Metrics: Concordance correlation coefficient (CCC)
• Facial Expression Recognition - Metrics: Accuracy (7 emotion)

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• QCS: Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition (2024) -
• ExpLLM: Towards Chain of Thought for Facial Expression Recognition (2024) -
• ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognition (2024) -
• Norface: Improving Facial Expression Analysis by Identity Normalization (2024) -
• Representation Learning and Identity Adversarial Training for Facial Behavior Understanding (2024) -
• Batch Transformer: Look for Attention in Batch (2024) -
• CAGE: Circumplex Affect Guided Expression Inference (2024) -
• From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos (2023) -
• POSTER++: A simpler and stronger facial expression recognition network (2023) -
• Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers (2022) -
• Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition (2022) -
• Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition (2021) -
• Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition (2021) -
• Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation (2021) -
• Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study (2021) -
• Facial expression and attributes recognition based on multi-task learning of lightweight neural networks (2021) -
• Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition (2021) -
• Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition (2020) -
• Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks (2020) -
• Compacting, Picking and Growing for Unforgetting Continual Learning (2019) -