Update README.md

README.md

@@ -65,4 +65,4 @@ Our contribution can be summarized as follows:
 - **🎯 Multi-Category Try-Off**. We present a unified framework capable of handling multiple garment types (upper-body, lower-body, and full-body clothes) without requiring category-specific pipelines.
 - **🔗 Multimodal Hybrid Attention**. We introduce a novel attention mechanism that integrates garment textual descriptions into the generative process by linking them with person-specific features. This helps the model synthesize occluded or ambiguous garment regions more accurately.
 - **⚡ Garment Aligner Module**. We design a lightweight aligner that conditions generation on clean garment images, replacing conventional denoising objectives. This leads to better alignment consistency on the overall dataset and preserves more precise visual retention.
-- **📊 Extensive experiments**. Experiments on the Dress Code and VITON-HD datasets demonstrate that TEMUVTOFF outperforms prior methods in both the quality of generated images and alignment with the target garment, highlighting its strong generalization capabilities.
+- **📊 Extensive experiments**. Experiments on the Dress Code and VITON-HD datasets demonstrate that TEMU-VTOFF outperforms prior methods in both the quality of generated images and alignment with the target garment, highlighting its strong generalization capabilities.