3 citations · 8 across the 7 of their papers we have counts for
7 papers
SANGRIA: Surgical Video Scene Graph Optimization for Surgical Workflow Prediction
Çağhan Köksal, Ghazal Ghazaei, Felix Holm +2
Graph-based holistic scene representations facilitate surgical workflow understanding and have recently demonstrated significant success. However, this task is often hindered by th…
PRISM: Progressive Restoration for Scene Graph-based Image Manipulation
Pavel Jahoda, Azade Farshad, Yousef Yeganeh +2
Scene graphs have emerged as accurate descriptive priors for image generation and manipulation tasks, however, their complexity and diversity of the shapes and relations of objects…
SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis
Azade Farshad, Yousef Yeganeh, Yu Chi +3
Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models con…
SCOPE: Structural Continuity Preservation for Medical Image Segmentation
Yousef Yeganeh, Azade Farshad, Goktug Guevercin +5
Although the preservation of shape continuity and physiological anatomy is a natural assumption in the segmentation of medical images, it is often neglected by deep learning method…
DIAMANT: Dual Image-Attention Map Encoders For Medical Image Segmentation
Yousef Yeganeh, Azade Farshad, Peter Weinberger +3
Although purely transformer-based architectures showed promising performance in many computer vision tasks, many hybrid models consisting of CNN and transformer blocks are introduc…
Shape-Aware Masking for Inpainting in Medical Imaging
Yousef Yeganeh, Azade Farshad, Nassir Navab
Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery. The masks used for inpainting are generally independen…