1 citations · 1 across the 10 of their papers we have counts for
10 papers
MidSteer: Optimal Affine Framework for Steering Generative Models
Tatiana Gaintseva, Andrew Stepanov, Ziquan Liu +4
Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment alignment and safety settings. However,…
Towards the Automatic Segmentation, Modeling and Meshing of the Aortic Vessel Tree from Multicenter Acquisitions: An Overview of the SEG.A. 2023 Segmentation of the Aorta Challenge
Yuan Jin, Antonio Pepe, Gian Marco Melito +36
The automated analysis of the aortic vessel tree (AVT) from computed tomography angiography (CTA) holds immense clinical potential, but its development has been impeded by a lack o…
CASteer: Cross-Attention Steering for Controllable Concept Erasure
Tatiana Gaintseva, Andreea-Maria Oncescu, Chengcheng Ma +5
Diffusion models have transformed image generation, yet controlling their outputs to reliably erase undesired concepts remains challenging. Existing approaches usually require task…
Multi-Frame Blind Manifold Deconvolution for Rotating Synthetic Aperture Imaging
Dao Lin, Jian Zhang, Martin Benning
Rotating synthetic aperture (RSA) imaging system captures images of the target scene at different rotation angles by rotating a rectangular aperture. Deblurring acquired RSA images…
Compositional Segmentation of Cardiac Images Leveraging Metadata
Abbas Khan, Muhammad Asad, Martin Benning +2
Cardiac image segmentation is essential for automated cardiac function assessment and monitoring of changes in cardiac structures over time. Inspired by coarse-to-fine approaches i…
Improving Interpretability and Robustness for the Detection of AI-Generated Images
Tatiana Gaintseva, Laida Kushnareva, German Magai +5
With growing abilities of generative models, artificial content detection becomes an increasingly important and difficult task. However, all popular approaches to this problem suff…
CAMS: Convolution and Attention-Free Mamba-based Cardiac Image Segmentation
Abbas Khan, Muhammad Asad, Martin Benning +2
Convolutional Neural Networks (CNNs) and Transformer-based self-attention models have become the standard for medical image segmentation. This paper demonstrates that convolution a…
Multi-view Cardiac Image Segmentation via Trans-Dimensional Priors
Abbas Khan, Muhammad Asad, Martin Benning +2
We propose a novel multi-stage trans-dimensional architecture for multi-view cardiac image segmentation. Our method exploits the relationship between long-axis (2D) and short-axis…
RAVE: Residual Vector Embedding for CLIP-Guided Backlit Image Enhancement
Tatiana Gaintseva, Martin Benning, Gregory Slabaugh
In this paper we propose a novel modification of Contrastive Language-Image Pre-Training (CLIP) guidance for the task of unsupervised backlit image enhancement. Our work builds on…
Crop and Couple: cardiac image segmentation using interlinked specialist networks
Abbas Khan, Muhammad Asad, Martin Benning +2
Diagnosis of cardiovascular disease using automated methods often relies on the critical task of cardiac image segmentation. We propose a novel strategy that performs segmentation…