DoRM: A Brain-Inspired Approach to Generative Domain Adaptation

Introducing Few-shot Generative Domain Adaptation (GDA) The challenge: Adapting a model trained on one type of data to perform well on another type, using only a few examples from the new type. Main Solution: Enhancing the Generator We focus on improving a special AI model called a “generator” to create new data samples that resemble the new target domain, using only a few examples. Addressing Challenges with DoRM Solution When the source and target domains are very different, problems arise. Domain Re-Modulation (DoRM) addresses these challenges by improving image synthesis quality, diversity, and cross-domain consistency. Key Innovations of DoRM - Source Generator Preparation - Introducing M&A Modules - Style Space Adjustment - Linear Domain Shift - Cross-Domain Consistency Enhancement Training Framework Evaluation and Conclusion DoRM demonstrated superior synthesis quality and cross-domain consistency compared to other methods, especially in domains like Sketches and FFHQ-Babies. It excelled in multi-domain and hybrid-domain generation, showcasing its ability to integrate diverse domains and synthesize novel hybrid outputs efficiently. DoRM: A Brain-Inspired Approach to Generative Domain Adaptation DoRM is a streamlined generator structure tailored for GDA, incorporating a novel similarity-based structure loss to ensure robust cross-domain consistency. The method demonstrates superior synthesis quality, diversity, and cross-domain consistency compared to existing approaches. AI Solutions for Your Company Discover how AI can redefine your way of work. Identify Automation Opportunities, Define KPIs, Select an AI Solution, and Implement Gradually. For AI KPI management advice, connect with us at hello@itinai.com. Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com. List of Useful Links: - AI Lab in Telegram @itinai – free consultation - Twitter – @itinaicom