VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models

• URL: http://arxiv.org/abs/2505.19571v1
• Date: Mon, 26 May 2025 06:37:11 GMT
• Title: VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models
• Authors: Hu Xiaobin, Liang Yujie, Luo Donghao, Peng Xu, Zhang Jiangning, Zhu Junwei, Wang Chengjie, Fu Yanwei,
• Abstract summary: We introduce VTBench, a hierarchical benchmark suite that decomposes virtual image try-on into hierarchical, disentangled dimensions.<n>The benchmark encompasses five critical dimensions for virtual try-on generation.<n> VTBench will be open-sourced, including all test sets, evaluation protocols, generated results, and human annotations.
• Score: 3.7098434045639874
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While virtual try-on has achieved significant progress, evaluating these models towards real-world scenarios remains a challenge. A comprehensive benchmark is essential for three key reasons:(1) Current metrics inadequately reflect human perception, particularly in unpaired try-on settings;(2)Most existing test sets are limited to indoor scenarios, lacking complexity for real-world evaluation; and (3) An ideal system should guide future advancements in virtual try-on generation. To address these needs, we introduce VTBench, a hierarchical benchmark suite that systematically decomposes virtual image try-on into hierarchical, disentangled dimensions, each equipped with tailored test sets and evaluation criteria. VTBench exhibits three key advantages:1) Multi-Dimensional Evaluation Framework: The benchmark encompasses five critical dimensions for virtual try-on generation (e.g., overall image quality, texture preservation, complex background consistency, cross-category size adaptability, and hand-occlusion handling). Granular evaluation metrics of corresponding test sets pinpoint model capabilities and limitations across diverse, challenging scenarios.2) Human Alignment: Human preference annotations are provided for each test set, ensuring the benchmark's alignment with perceptual quality across all evaluation dimensions. (3) Valuable Insights: Beyond standard indoor settings, we analyze model performance variations across dimensions and investigate the disparity between indoor and real-world try-on scenarios. To foster the field of virtual try-on towards challenging real-world scenario, VTBench will be open-sourced, including all test sets, evaluation protocols, generated results, and human annotations.

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