3 citations · 8 across the 13 of their papers we have counts for
13 papers
MixFlow: Mixed Source Distributions Improve Rectified Flows
Nazir Nayal, Christopher Wewer, Jan Eric Lenssen
Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative sampling caused by the highl…
SceneTok: A Compressed, Diffusable Token Space for 3D Scenes
Mohammad Asim, Christopher Wewer, Jan Eric Lenssen
We present SceneTok, a novel tokenizer for encoding view sets of scenes into a compressed and diffusable set of unstructured tokens. Existing approaches for 3D scene representation…
SemanticNVS: Improving Semantic Scene Understanding in Generative Novel View Synthesis
Xinya Chen, Christopher Wewer, Jiahao Xie +2
We present SemanticNVS, a camera-conditioned multi-view diffusion model for novel view synthesis (NVS), which improves generation quality and consistency by integrating pre-trained…
Spatial Reasoners for Continuous Variables in Any Domain
Bart Pogodzinski, Christopher Wewer, Bernt Schiele +1
We present Spatial Reasoners, a software framework to perform spatial reasoning over continuous variables with generative denoising models. Denoising generative models have become…
Spatial Reasoning with Denoising Models
Christopher Wewer, Bart Pogodzinski, Bernt Schiele +1
We introduce Spatial Reasoning Models (SRMs), a framework to perform reasoning over sets of continuous variables via denoising generative models. SRMs infer continuous representati…
MEt3R: Measuring Multi-View Consistency in Generated Images
Mohammad Asim, Christopher Wewer, Thomas Wimmer +2
We introduce MEt3R, a metric for multi-view consistency in generated images. Large-scale generative models for multi-view image generation are rapidly advancing the field of 3D inf…
Spurfies: Sparse Surface Reconstruction using Local Geometry Priors
Kevin Raj, Christopher Wewer, Raza Yunus +2
We introduce Spurfies, a novel method for sparse-view surface reconstruction that disentangles appearance and geometry information to utilize local geometry priors trained on synth…
Sp2360: Sparse-view 360 Scene Reconstruction using Cascaded 2D Diffusion Priors
Soumava Paul, Christopher Wewer, Bernt Schiele +1
We aim to tackle sparse-view reconstruction of a 360 3D scene using priors from latent diffusion models (LDM). The sparse-view setting is ill-posed and underconstrained, especially…
latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction
Christopher Wewer, Kevin Raj, Eddy Ilg +2
We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that can be splatted and decoded by a light-weight generative 2D architecture. Existing methods…
Neural Point Cloud Diffusion for Disentangled 3D Shape and Appearance Generation
Philipp Schröppel, Christopher Wewer, Jan Eric Lenssen +2
Controllable generation of 3D assets is important for many practical applications like content creation in movies, games and engineering, as well as in AR/VR. Recently, diffusion m…
Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction
Devikalyan Das, Christopher Wewer, Raza Yunus +2
Reconstructing dynamic objects from monocular videos is a severely underconstrained and challenging problem, and recent work has approached it in various directions. However, owing…
SimNP: Learning Self-Similarity Priors Between Neural Points
Christopher Wewer, Eddy Ilg, Bernt Schiele +1
Existing neural field representations for 3D object reconstruction either (1) utilize object-level representations, but suffer from low-quality details due to conditioning on a glo…
Updating Embeddings for Dynamic Knowledge Graphs
Christopher Wewer, Florian Lemmerich, Michael Cochez
Data in Knowledge Graphs often represents part of the current state of the real world. Thus, to stay up-to-date the graph data needs to be updated frequently. To utilize informatio…