Generating high-quality and diverse human images is an important yet challenging task in
vision and graphics. However, existing generative models often fall short under the high …

Deep person generation has attracted extensive research attention due to its wide
applications in virtual agents, video conferencing, online shopping, and art/movie …

Image-based virtual try-on strives to transfer the appearance of a clothing item onto the
image of a target person. Existing literature focuses mainly on upper-body clothes (eg t …

Diffusion probabilistic models (DPMs) have become a popular approach to conditional
generation, due to their promising results and support for cross-modal synthesis. A key …

Appearance and pose-guided human generation is a burgeoning field that has captured
significant attention. This subject's primary objective is to transfer pose information from a …

Controllable person image synthesis aims at rendering a source image based on user-
specified changes in body pose or appearance. Prior art approaches leverage pixel-level …

Recent advances in neural models have shown great results for virtual try-on (VTO)
problems, where a 3D representation of a garment is deformed to fit a target body shape …

Virtual try-on tasks aim at synthesizing realistic try-on results by trying target clothes on
humans. Most previous works relied on the Thin Plate Spline or appearance flows to warp …

Most existing methods for virtual try-on focus on studio person images with a limited range of
poses and clean backgrounds. They can achieve plausible results for this studio try-on …

In this paper, a novel virtual try-on algorithm, dubbed SAL-VTON, is proposed, which links
the garment with the person via semantically associated landmarks to alleviate …