1 citations · 2 across the 4 of their papers we have counts for
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Explaining Image Similarity with Automatically Extracted Concept Activation Vectors
Isaac Roberts, Petra Bevandic, Alexander Schulz +1
Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing explainability methods often r…
MGT: Extending Virtual Try-Off to Multi-Garment Scenarios
Riza Velioglu, Petra Bevandic, Robin Chan +1
Computer vision is transforming fashion industry through Virtual Try-On (VTON) and Virtual Try-Off (VTOFF). VTON generates images of a person in a specified garment using a target…
TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models
Riza Velioglu, Petra Bevandic, Robin Chan +1
This paper introduces Virtual Try-Off (VTOFF), a novel task generating standardized garment images from single photos of clothed individuals. Unlike Virtual Try-On (VTON), which di…
Automatic universal taxonomies for multi-domain semantic segmentation
Petra Bevandić, Siniša Šegvić
Training semantic segmentation models on multiple datasets has sparked a lot of recent interest in the computer vision community. This interest has been motivated by expensive anno…