ShoeFit: A New Dataset and Dual-image-stream DiT Framework for Virtual Footwear Try-On

(b) ShoeFit has demonstrated excellent preservation of the fidelity of footwear across real-world scenes.

†Work done during an internship at Alibaba. ‡Corresponding author.

39th Conference on Neural Information Processing Systems (NeurIPS 2025).

footwear latents. The proposed framework effectively decouples shoe appearance from environmental interferences while preserving high-quality texture detail through decoupled denoising and conditioning branches. Extensive quantitative and qualitative experiments demonstrate that our method substantially improves rendering fidelity and robustness under challenging real-world product shoes, establishing a new benchmark in high-fidelity footwear try-on synthesis. The dataset and benchmark will be publicly available upon acceptance of the paper.