1.3k citations · 1.5k across the 47 of their papers we have counts for
10 papers · 2 filters
SLayR: Scene Layout Generation with Rectified Flow
Cameron Braunstein, Hevra Petekkaya, Jan Eric Lenssen +2
We introduce SLayR, Scene Layout Generation with Rectified flow, a novel transformer-based model for text-to-layout generation which can then be paired with existing layout-to-imag…
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…
InterTrack: Tracking Human Object Interaction without Object Templates
Xianghui Xie, Jan Eric Lenssen, Gerard Pons-Moll
Tracking human object interaction from videos is important to understand human behavior from the rapidly growing stream of video data. Previous video-based methods require predefin…
Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets
Wolfgang Boettcher, Lukas Hoyer, Ozan Unal +2
In this work, we introduce Scribbles for All, a label and training data generation algorithm for semantic segmentation trained on scribble labels. Training or fine-tuning semantic…
Improving 2D Feature Representations by 3D-Aware Fine-Tuning
Yuanwen Yue, Anurag Das, Francis Engelmann +2
Current visual foundation models are trained purely on unstructured 2D data, limiting their understanding of 3D structure of objects and scenes. In this work, we show that fine-tun…
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…
GEARS: Local Geometry-aware Hand-object Interaction Synthesis
Keyang Zhou, Bharat Lal Bhatnagar, Jan Eric Lenssen +1
Generating realistic hand motion sequences in interaction with objects has gained increasing attention with the growing interest in digital humans. Prior work has illustrated the e…
NRDF: Neural Riemannian Distance Fields for Learning Articulated Pose Priors
Yannan He, Garvita Tiwari, Tolga Birdal +2
Faithfully modeling the space of articulations is a crucial task that allows recovery and generation of realistic poses, and remains a notorious challenge. To this end, we introduc…
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…
Recent Trends in 3D Reconstruction of General Non-Rigid Scenes
Raza Yunus, Jan Eric Lenssen, Michael Niemeyer +7
Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision. It enables the synthe…