Multimodal Edge-to-RGB Image Translation

Designed an encoder-decoder architecture using cVAE and GAN to convert edge images into realistic RGB images, enhancing scene interpretation.

Improved output diversity and realism by incorporating latent space sampling and multimodal learning, achieving high-quality image generation with better adaptability in dynamic environments.