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Found 5 papers, 2 papers with code
Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion Recognition
This article presents our results for the eighth Affective Behavior Analysis in-the-wild (ABAW) competition. Multimodal emotion recognition (ER) has important applications in affective computing and human-computer interaction.
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
In this paper, we focus on how to improve the performance of the draft model and aim to accelerate inference via a high acceptance rate.
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition
However, this process may lead to inaccurate annotations, such as ignoring non-majority or non-candidate labels.
Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild
Multimodal fusion is a significant method for most multimodal tasks.
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition
To bridge this gap, we present the quantitative evaluation results of GPT-4V on 21 benchmark datasets covering 6 tasks: visual sentiment analysis, tweet sentiment analysis, micro-expression recognition, facial emotion recognition, dynamic facial emotion recognition, and multimodal emotion recognition.
