5 papers · 1 filter
From Imitation to Innovation: The Emergence of AI Unique Artistic Styles and the Challenge of Copyright Protection
Zexi Jia, Chuanwei Huang, Yeshuang Zhu +6
Current legal frameworks consider AI-generated works eligible for copyright protection when they meet originality requirements and involve substantial human intellectual input. How…
A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets
Zexi Jia, Chuanwei Huang, Hongyan Fei +6
Vision-language models (VLMs) often struggle with compositional reasoning due to insufficient high-quality image-text data. To tackle this challenge, we propose a novel block-based…
Synthetic Data RL: Task Definition Is All You Need
Yiduo Guo, Zhen Guo, Chuanwei Huang +5
Reinforcement learning (RL) is a powerful way to adapt foundation models to specialized tasks, but its reliance on large-scale human-labeled data limits broad adoption. We introduc…
Control-CLIP: Decoupling Category and Style Guidance in CLIP for Specific-Domain Generation
Zexi Jia, Chuanwei Huang, Hongyan Fei +4
Text-to-image diffusion models have shown remarkable capabilities of generating high-quality images closely aligned with textual inputs. However, the effectiveness of text guidance…
Semantic to Structure: Learning Structural Representations for Infringement Detection
Chuanwei Huang, Zexi Jia, Hongyan Fei +4
Structural information in images is crucial for aesthetic assessment, and it is widely recognized in the artistic field that imitating the structure of other works significantly in…