This topic surveys image generation tools used in 2026 to produce photorealistic visuals, enable virtual try‑ons, and plug generated assets into marketing and commerce workflows while addressing legal and operational safeguards. Advances in generative models have pushed photorealism into mainstream retail use—on‑model renders, avatar-based try‑ons, and style transfers are now core capabilities that reduce photography costs and speed creative iteration. Key tool categories include virtual stylists and avatar try‑on platforms (e.g., LookBook AI), visual commerce and on‑model rendering systems (Veesual), portrait editors and avatar generators (1PX.AI — currently unreachable but cited in third‑party sources), apparel design-to‑production services (Pixite), and marketing automation that pairs visuals with campaign content (Migma AI). Relevance in 2026 comes from tighter integration of image generators into end‑to‑end commerce and marketing stacks: assets are generated, variant tested, attributed in campaigns, and routed to production or personalization engines. That integration raises operational priorities—workflow compatibility (APIs, asset tagging, A/B testing support), versioning and provenance (model/source metadata), and legal safeguards such as consent for likeness use, copyright checks, and clear licensing terms. Tool reliability and data governance matter too: the unreachability of some vendor sites (e.g., 1PX.AI) underscores vendor due diligence and continuity planning. This overview helps teams evaluate tradeoffs—photorealism vs. control, on‑brand automation vs. manual review, and in‑house hosting vs. SaaS—while emphasizing practical considerations for adoption: integration into marketing attribution, compliance with IP/consent requirements, and production workflows that move generated images from prototype to live commerce assets.