mlsanityData to 7 Oct 2026

Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias

arXiv 1808.02212 ↗First posted 7 Aug 2018cs.CVcited by 41

Not on the map. Why?

Abstract (arXiv)

While machine learning approaches to visual emotion recognition offer great promise, current methods consider training and testing models on small scale datasets covering limited visual emotion concepts. Our analysis identifies an important but long overlooked issue of existing visual emotion benchmarks in the form of dataset biases. We design a series of tests to show and measure how such dataset biases obstruct learning a generalizable emotion recognition model. Based on our analysis, we propose a webly supervised approach by leveraging a large quantity of stock image data. Our approach uses a simple yet effective curriculum guided training strategy for learning discriminative emotion features. We discover that the models learned using our large scale stock image dataset exhibit significantly better generalization ability than the existing datasets without the manual collection of even a single label. Moreover, visual representation learned using our approach holds a lot of promise across a variety of tasks on different image and video datasets.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Aug 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 5; 2023: 7; 2024: 6; 2025: 7; 2026: 7.

41 papers.

Sort:

By area:

  1. 2022Exploring CLIP for Assessing the Look and Feel of Imagescited by 974
  2. 2024Visual In-Context Learning for Large Vision-Language Modelscited by 124
  3. 2021A Survey on Bias in Visual Datasetscited by 84
  4. 2023PromptMagician: Interactive Prompt Engineering for Text-to-Image Creationcited by 58
  5. 2021Affective Image Content Analysis: Two Decades Review and New Perspectivescited by 47
  6. 2024EmoVIT: Revolutionizing Emotion Insights with Visual Instruction Tuningcited by 42
  7. 2023Context De-confounded Emotion Recognitioncited by 34
  8. 2021Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimizationcited by 32
  9. 2022MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysiscited by 29
  10. 2021Affect2MM: Affective Analysis of Multimedia Content Using Emotion Causalitycited by 17
  11. 2025Knowledge-Aligned Counterfactual-Enhancement Diffusion Perception for Unsupervised Cross-Domain Visual Emotion Recognitioncited by 16
  12. 2021Exploring Visual Engagement Signals for Representation Learningcited by 12
29 more
  1. 2021Towards Unbiased Visual Emotion Recognition via Causal Interventioncited by 11
  2. 2024Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Trainingcited by 11
  3. 2025MAPO: Mixed Advantage Policy Optimizationcited by 11
  4. 2025EmoArt: A Multidimensional Dataset for Emotion-Aware Artistic Generationcited by 10
  5. 2022Bias Reducing Multitask Learning on Mental Health Predictioncited by 9
  6. 2021Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasingcited by 6
  7. 2023How you feelin'? Learning Emotions and Mental States in Movie Scenescited by 6
  8. 2026Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarkscited by 6
  9. 2023Socratis: Are large multimodal models emotionally aware?cited by 5
  10. 2023On the use of Vision-Language models for Visual Sentiment Analysis: a study on CLIPcited by 5
  11. 2022A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigmscited by 4
  12. 2022AU-Aware Vision Transformers for Biased Facial Expression Recognitioncited by 4
  13. 2023Using Positive Matching Contrastive Loss with Facial Action Units to mitigate bias in Facial Expression Recognitioncited by 4
  14. 2024Delving Deep into Engagement Prediction of Short Videoscited by 4
  15. 2023Impressions: Understanding Visual Semiotics and Aesthetic Impactcited by 3
  16. 2024UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perceptioncited by 3
  17. 2025Customizing Visual Emotion Evaluation for MLLMs: An Open-vocabulary, Multifaceted, and Scalable Approachcited by 3
  18. 2025EmoCaliber: Advancing Reliable Visual Emotion Comprehension via Confidence Verbalization and Calibrationcited by 3
  19. 2025Bridging Visual Affective Gap: Borrowing Textual Knowledge by Learning from Noisy Image-Text Pairscited by 2
  20. 2021Analyzing Images for Music Recommendationcited by 0
  21. 2021Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysiscited by 0
  22. 2024TinyEmo: Scaling down Emotional Reasoning via Metric Projectioncited by 0
  23. 2025Attributes-aware Visual Emotion Representation Learningcited by 0
  24. 2026What Are We Really Measuring? Rethinking Dataset Bias in Web-Scale Natural Image Collections via Unsupervised Semantic Clusteringcited by 0
  25. 2026Attribute-Grounded Selective Reasoning for Artwork Emotion Understanding with Multimodal Large Language Modelscited by 0
  26. 2026ArtECulture: Benchmarking Culture-Conditioned Visual Emotion Understanding in Multimodal Large Language Modelscited by 0
  27. 2026MAG: MAnifold Guided Semi-Supervised Multi-modal In-Context Learningcited by 0
  28. 2026DSPO: Diversity-aware Subjective Policy Optimization for Robust Emotional Reasoningcited by 0
  29. 2026Decoding Affective Nuances: Enhancing MLLMs via Hierarchical Emotion Reasoning and Contrastive Discriminative Pruningcited by 0