Основні поняття
GPT-4V demonstrates strong visual understanding capabilities in Generalized Emotion Recognition tasks, but struggles with specialized knowledge like micro-expressions.
Анотація
This article evaluates GPT-4V's performance in emotion recognition tasks across various datasets. It discusses the model's ability to integrate multimodal clues and exploit temporal information. The study highlights the limitations of GPT-4V in recognizing micro-expressions and provides insights into potential future research directions.
Structure:
- Introduction:
- Discusses the importance of emotion recognition and introduces Generalized Emotion Recognition (GER) tasks.
- Related Works:
- Explores different tasks within GER and their distinctions.
- Task Description:
- Details each task and dataset used for evaluation.
- GPT-4V Calling Strategy:
- Describes the strategy designed for handling requests in GER tasks.
- Results and Discussion:
- Presents main results, including comparisons with baselines and supervised systems.
- Temporal Modeling Ability:
- Evaluates GPT-4V's performance based on sampling frames in dynamic facial emotion recognition.
- Multimodal Fusion Ability:
- Examines GPT-4V's ability to integrate multimodal information in emotion recognition tasks.
- System Stability:
- Analyzes the stability of GPT-4V predictions through multiple runs.
- Class-wise Performance Analysis:
- Visualizes confusion matrices to analyze class-wise prediction consistency.
- Robustness to Template Change:
- Explores how changes in prompt templates affect GPT-4V's performance.
- Robustness to Color Space:
- Evaluates GPT-4V's robustness to color space changes using grayscale images.
- Security Check:
- Discusses instances where security checks impact model predictions.
- Case Study:
- Provides examples of incorrect predictions made by GPT-4V in different tasks.
Статистика
この論文は、GPT-4Vの評価結果に基づいて、様々なデータセットで感情認識タスクのパフォーマンスを評価しています。
Цитати
"Through experimental analysis, we observe that GPT-4V exhibits strong visual understanding capabilities in GER tasks."
"GPT-4V is primarily designed for general domains and cannot recognize micro-expressions that require specialized knowledge."