MooD: Perception-Enhanced Efficient Affective Image Editing via Continuous Valence-Arousal Modeling

arXiv:2605.02521 · cs.CV · Submitted 2026-05-04 · Read on arXiv

cs.CV

Submitted: 2026-05-04

Updated: 2026-09-26

Terminology

• Affective Image Editing — 10× in this paper
• Ablation — 8× in this paper · explained in 1 episode
• Consistency — 8× in this paper · explained in 3 episodes
• Diffusion Model — 8× in this paper · explained in 8 episodes
• Diffusion Models — 8× in this paper · explained in 6 episodes
• Computer Vision and Pattern Recognition — 6× in this paper
• Embeddings — 6× in this paper · explained in 2 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• Affective Computing — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Hallucination — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Agentic Reasoning — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Semantic Gap — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes

Sources

• Improving Multimodal Sentiment Analysis via Modality Optimization and Dynamic Primary Modality Selection
• EmoKGEdit: Training-free Affective Injection via Visual Cue Transformation
• ViC-Bench: Benchmarking Visual-Interleaved Chain-of-Thought Capability in MLLMs with Free-Style Intermediate State Representations
• Qwen2.5-VL Technical Report
• eMotions: A Large-Scale Dataset and Audio-Visual Fusion Network for Emotion Analysis in Short-form Videos
• SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
• Step1X-Edit: A Practical Framework for General Image Editing
• Decoupled Weight Decay Regularization

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