🏢 University of Tübingen

µP²: Layerwise perturbation scaling in SAM enables hyperparameter transfer and improved generalization in large models.

Real-time rendering of objects with subsurface scattering effects is now possible with SSS-GS, a novel method combining explicit surface geometry and implicit subsurface scattering for high-quality no…

Sourcerer: A novel sample-based method for maximum entropy source distribution estimation, resolving ill-posedness while maintaining simulation accuracy.

Neuroscience-inspired motion energy processing enables human-like zero-shot generalization in figure-ground segmentation, outperforming deep learning models on random dot stimuli.

Neural Localizer Fields (NLF) revolutionizes 3D human pose and shape estimation by learning a continuous field of point localizer functions, enabling flexible training on diverse data and on-the-fly p…

LDNS: a new generative model for neural spiking data, enabling high-fidelity sampling and low-dimensional latent inference, paving the way for simulating realistic brain activity.

Human-3Diffusion generates realistic 3D avatars from single RGB images using coupled 2D multi-view and 3D consistent diffusion models, achieving high-fidelity geometry and texture.