Understand
In this paper, we present TextCrafter, a Complex Visual Text Generation (CVTG) framework inspired by selective visual attention in cognitive science, and introduce the "Text Insulation-and-Attention" mechanisms.
- To implement the selective-attention principle that selection operates on discrete objects, we propose a novel Bottleneck-aware Constrained Reinforcement Learning for Multi-text Insulation, which substantially improves text-rendering performance on the strong Qwen-Image pretrained model without introducing additional parameters.
- To align with the selective concentration principle in human vision, we introduce a text-oriented attention module with a novel Quotation-guided Attention Gate that further improves generation quality for each text instance.
- Our Reinforcement Learning based text insulation approach attains state-of-the-art results, and incorporating text-oriented attention yields additional gains on top of an already strong baseline.