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Class Activation Mapping in Explainable Computer Vision: A Method-Centered Review of CNN, Transformer, and Foundation-Model-Era Visual Explanations
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- A comprehensive review of class activation mapping methods for explaining computer vision models, covering CNNs, transformers, and foundation models across 57 papers since 2016.
- Why it matters
- Relevant for engineers building or auditing vision systems who need to understand which explanation techniques apply to their model architecture and use case.
- Watch out
- Evaluation metrics for explanation quality remain fragmented across studies, making it difficult to directly compare methods on faithfulness, robustness, or human trust.
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