736 citations · 1.1k across the 52 of their papers we have counts for
71 papers
Improved Distributional Diffusion Models
Tommaso Martorella, Alexandre Galashov, Felix Krause +4
Distributional Diffusion Models (DDMs) replace the standard mean-prediction denoiser with a \emph{distributional} denoiser trained via a scoring rule objective, learning a stochast…
Logit Refiner: Improving Visual Autoregressive Models via Intra-Scale Dependency Modeling
Meimingwei Li, Stefan Andreas Baumann, Felix Krause +1
Visual Autoregressive Models (VAR) generate images through next-scale prediction, producing all tokens within each scale in parallel. We show that this parallel decoding constitute…
What Moves? Localized Motion Representations for Compositional Scene Control
Frank Fundel, Malek Ben Alaya, Thomas Ressler-Antal +2
Real-world dynamics are inherently compositional: multiple entities move simultaneously within a shared scene, each exhibiting distinct motion patterns. Yet current motion represen…
Concept Guidance: Precise, Training-Free Latent Control for Text-to-Image Generation
Nikolai Röhrich, Isabell Hans, Felix Krause +1
Text-to-image diffusion models have two major drawbacks that severely limit their practical utility: (1) standard models lack an intrinsic mechanism for continuous, concept-specifi…
Schrödinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics
Timy Phan, Jannik Wiese, Björn Ommer
Predicting how a scene may evolve from partial observations requires reasoning about multiple possible futures rather than committing to a single trajectory. Existing approaches ei…
Show Me Examples: Inferring Visual Concepts from Image Sets
Nick Stracke, Kolja Bauer, Stefan Andreas Baumann +3
Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, current models fail to infer shared co…