Tencent has embarked on an eye-catching research project—Virtual Dressing (VD). This creative task is designed to produce human images with a high degree of customization. In these images, the clothing is set as a key element, while other elements such as the person's face, posture, and background can be flexibly adjusted according to actual needs.
At the same time, Tencent's research team has also meticulously developed an evaluation system called the "Comprehensive Affinity Metric Index" (CAMI). This evaluation system plays a crucial role as it can accurately measure the consistency between the generated image and the reference clothing. Through this index, the effectiveness of virtual dressing technology can be objectively assessed, providing a strong basis for further optimization and improvement.
Among them, IMAGDressing-v1 demonstrates a significant advantage. It can seamlessly integrate with other AI model expansion plugins (such as ControlNet and IP-Adapter). This integration brings multiple benefits, further enhancing the diversity and controllability of the generated images. It makes the generated human images more colorful and capable of meeting the personalized needs of different users in various scenarios.