Latest Research in Computer Vision and Pattern Recognition
17 research papers · 0.1 average citations · 2026 median publication year
Top Research Topics in Computer Vision and Pattern Recognition
- Computer Vision and Pattern Recognition — 5 papers
- Computation and Language — 3 papers
- Emotion and Mood Recognition — 2 papers
- Artificial Intelligence — 2 papers
- Language, Linguistics, Cultural Analysis — 2 papers
- Hate Speech and Cyberbullying Detection — 1 papers
- Sound — 1 papers
- Sentiment Analysis and Opinion Mining — 1 papers
Highest-Cited Papers
- moroccan_nlp: Linguistic Resources and Models for Moroccan Darija and Arabic (1 citations)
- MVEI & EmObserver: Empowering MLLM-Oriented Visual Emotional Intelligence via Emotion Statement Judgement
- Tears or Cheers? Benchmarking LLMs via Culturally Elicited Distinct Affective Responses
- Multimodal Hateful Meme Detection Model Exploiting Attention-Based Gating Fusion of Global-Local-Context Information
- Style over Substance: A Shortcut Audit of Emotion-Description Preference Evaluation
- TellTale: Blending Multi-Instance LoRA Text Encoders and a Zero-Shot LLM Judge for Ambivalence/Hesitancy Recognition in Videos
- GHMCL: A diffusion-based generative hypergraph framework with multi-Scale contrastive learning
- Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?
- Learning When to Feel: Scalar-Gated Fusion and Affective Flow Representations
- CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection
- Simple Features and Honest Calibration for Ambivalence and Hesitancy Recognition in Video
- SHAP-Weighted Cross-Modal Expert Fusion for Emotion and Sentiment Recognition: Evidence and Limits
- Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wild
- moroccan_nlp: Linguistic Resources and Models for Moroccan Darija and Arabic (1 citations)
- When Emotions Conflict: A Reliability-Aware Framework for Arabic Multi-Label Emotion Detection
- Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies
- Faithful by Definition: Emotion Analysis via Natural Semantic Metalanguage Explications