CatVTON is a virtual try-on diffusion model published at ICLR 2025 that transfers clothing from a reference image onto a person. The model uses a concatenation-based approach to combine person and garment features, requiring only 8GB VRAM for inference at 1024x768 resolution. It offers parameter-efficient training with 49.57M trainable parameters out of 899.06M total parameters.