1 citations · 1 across the 4 of their papers we have counts for
4 papers
AlignFace: Human-Aligned Face Similarity Metric with Interpretable Concept Relations
Ying Huang, Wencan Zhang, Brian Y. Lim
Computer vision models for generated facial content, such as face editing and privacy protection, increasingly affect people, requiring similarity metrics that serve as faithful pr…
SketchXplain: Intuitive Visual Explanations of Image Classifiers with Sketches
Wencan Zhang, Mario Michelessa, Xuejun Zhao +1
Saliency map visualizations explain image-based AI predictions by pointing to regions, but these are often unintuitive and semantically unclear, leaving an interpretability gap. We…
Varif.ai to Vary and Verify User-Driven Diversity in Scalable Image Generation
M. Michelessa, J. Ng, C. Hurter +1
Diversity in image generation is essential to ensure fair representations and support creativity in ideation. Hence, many text-to-image models have implemented diversification mech…
Incremental XAI: Memorable Understanding of AI with Incremental Explanations
Jessica Y. Bo, Pan Hao, Brian Y. Lim
Many explainable AI (XAI) techniques strive for interpretability by providing concise salient information, such as sparse linear factors. However, users either only see inaccurate…