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---
name: modality_feature_fusion
description: Fuse paired infrared and visible arrays while preserving thermal salience and visible texture through controllable local/global weights.
---
# Modality Feature Fusion
## When To Use
Use this skill for bounded infrared-visible image-fusion analysis derived from `arXiv:2206.09581`, especially when preserving modality-specific features, comparing explicit/implicit mechanisms, or running proxy recovery.
## Inputs
See the corresponding module document in the attempt directory. Inputs must be local text or numeric arrays; do not read any original paper repository.
## Outputs
The skill returns deterministic JSON-compatible diagnostics suitable for downstream recovery and analysis.
## Workflow
1. Validate input shapes or text content.
2. Execute the module-specific mechanism with deterministic defaults.
3. Return compact evidence and numeric diagnostics.
4. For recovery, keep proxy/reduced labels explicit.
## Validation
Run `python /share/project/yuyang/workspace/Paper2Skills/Paper2Skills-Agent/src/packages/paper2skills-agent/src/paper2skills/skills/module-to-skill/scripts/validate_skill_tree.py /share/project/yuyang/workspace/Paperbench/record/case13/extracted_skills_attempt_001/exorl_unsupervised_rl/modality_feature_fusion --run-tests`.
## Limitations
This skill implements a lightweight, reusable proxy for the paper mechanism, not the full 21-test-set benchmark from the paper.
