Hierarchical Cross-Attention Network for Virtual Try-On
원문 초록
In this paper, we present an innovative solution for the challenges of the virtual try-on task: our novel Hierarchical Cross-Attention Network (HCANet). HCANet is crafted with two primary stages: geometric matching and try-on, each playing a crucial role in delivering realistic virtual try-on outcomes. A key feature of HCANet is the incorporation of a novel Hierarchical Cross-Attention (HCA) block into both stages, enabling the effective capture of long-range correlations between individual and clothing modalities. The HCA block enhances the depth and robustness of the network. By adopting a hierarchical approach, it facilitates a nuanced representation of the interaction between the person and clothing, capturing intricate details essential for an authentic virtual try-on experience. Our experiments establish the prowess of HCANet. The results showcase its performance across both quantitative metrics and subjective evaluations of visual realism. HCANet stands out as a state-of-the-art solution, demonstrating its capability to generate virtual try-on results that excel in accuracy and realism. This marks a significant step in advancing virtual try-on technologies.
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C-VTON: Context-Driven Image-Based Virtual Try-On Network
Toward Characteristic-Preserving Image-based Virtual Try-On Network
Arbitrary Virtual Try-On Network: Characteristics Preservation and Trade-off between Body and Clothing
SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On
Real-Time Per-Garment Virtual Try-On with Temporal Consistency for Loose-Fitting Garments
Low-Barrier Dataset Collection with Real Human Body for Interactive Per-Garment Virtual Try-On
토론
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