Do Virtual Try-Ons Fit True to Size? Science vs Perception

Virtual try-on measurement accuracy depends heavily on the specific technology employed. Advanced photo-based AI systems, like those used by Fytted, can achieve accuracy within 1-2 centimeters of professional manual measurements for key body dimensions such as bust, waist, and hips, according to a 2025 IEEE Conference on Computer Vision and Pattern Recognition benchmark study.

Simpler systems relying on basic image analysis may deviate by 5-10 cm or more, while video-based systems and smartphone depth sensors typically fall between these extremes. For general apparel sizing, advanced virtual try-on measurements are highly accurate and reliable, but custom tailoring requiring sub-centimeter precision still benefits from professional manual measurement.

Accurately predicting fabric drape remains one of virtual try-on technology's most significant challenges, though progress continues. Simulating complex fabric physics—how materials hang, fold, and move with gravity and body shape—requires intensive computation and detailed material property information.

A 2025 Textile Research Journal study found current systems achieve moderate success (60-70% realism rating) with common fabrics like cotton jersey or denim, but struggle significantly with complex materials like silk, chiffon, heavy knits, or embellished fabrics. While visual realism improves, accurately predicting fabric feel and subtle movement remains largely beyond current capabilities.

Virtual try-on performance can vary across different body types, though leading platforms actively work to improve inclusivity and consistency. Most systems are initially trained using datasets that may not fully represent human body shape and size diversity.

Platforms like Fytted, which use customer photos and extract detailed measurements, generally perform better across wider body type ranges because they capture individual nuances rather than relying on generic models. While technology becomes more inclusive, users across the body spectrum should be aware that accuracy might vary and benefit from combining virtual try-on insights with detailed size charts and customer reviews.

Vanity sizing significantly complicates virtual try-on accuracy and reliability. This practice of labeling clothes with sizes smaller than actual measurements creates inconsistency that affects system performance. When systems use accurate body measurements but compare them against inaccurate brand sizing information, fit predictions become misleading.

Advanced platforms mitigate this issue through several approaches. Some, like Fytted, build independent databases of actual garment measurements, bypassing potentially inaccurate brand size charts. Others use machine learning trained on purchase and return data to learn actual fit characteristics, effectively correcting for vanity sizing patterns.

Yes, virtual try-on accuracy and reliability tend to be better for certain clothing types compared to others, primarily due to garment structure complexity and fabric behavior differences. According to Forrester Research's 2025 Retail Technology Benchmark, virtual try-on technology performs best with structured or semi-structured garments having relatively predictable shapes and minimal drape.

Examples include blazers, tailored trousers, jeans, button-up shirts, and A-line skirts, achieving 85-90% fit prediction accuracy. Conversely, accuracy tends to be lower for garments with complex draping, significant stretch, unstructured designs, or intricate details, often achieving 60-75% accuracy range.

Whether to trust virtual try-on for expensive or special occasion outfits depends on the specific technology used, garment nature, and your tolerance for potential fit discrepancies. For high-value purchases where precise fit is critical, using virtual try-on as one component of your decision-making process is advisable.

Advanced virtual try-on solutions, especially those like Fytted using precise measurements and real customer images, can provide valuable insights that significantly reduce poor fit risk. For expensive items, complement virtual try-on with additional resources: carefully review detailed garment measurements, read customer reviews focusing on fit, understand brand-specific sizing reputation, and be fully aware of return policies.