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20182026
most citedFrom Variational to Deterministic Autoencoders

103 citations · 103 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

nnFoundation: 3D Foundation Models for Radiology

Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80

Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…

cs.CV2026

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

Asbjørn Munk, Stefano Cerri, Vardan Nersesjan +81

Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is heterogeneous and noisy, and high-quality labels are prohibitively costly to obt…

cs.CV2025

Moving by Looking: Towards Vision-Driven Avatar Motion Generation

Markos Diomataris, Berat Mert Albaba, Giorgio Becherini +3

The way we perceive the world fundamentally shapes how we move, whether it is how we navigate in a room or how we interact with other humans. Current human motion generation method…

cs.CV2024

RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks

Partha Ghosh, Soubhik Sanyal, Cordelia Schmid +1

We present a novel unconditional video generative model designed to address long-term spatial and temporal dependencies, with attention to computational and dataset efficiency. To…

cs.CV2021

InvGAN: Invertible GANs

Partha Ghosh, Dominik Zietlow, Michael J. Black +2

Generation of photo-realistic images, semantic editing and representation learning are a few of many potential applications of high resolution generative models. Recent progress in…