1 citations · 2 across the 8 of their papers we have counts for
9 papers · 1 filter
V-REX: Efficient Specialist VLM Training for Veterinary X-Rays
Tim Elsner, Nicole McNally, Andre Dourson +1
While generalist VLMs are expensive to train, creating domain experts is widely assumed to require fine-tuning increasingly large foundation models. We show that, in veterinary rad…
Prompting Image Generators for Training-free Primitive Shape Abstraction
Gregor Kobsik, Tim Elsner, Leif Kobbelt
Compact primitive abstractions represent 3D shapes with a few geometric primitives while preserving recognizable components. Learned methods depend on their training classes, and o…
Learning Fine-to-Coarse Cuboid Shape Abstraction
Gregor Kobsik, Morten Henkel, Yanjiang He +4
The abstraction of 3D objects with simple geometric primitives like cuboids allows to infer structural information from complex geometry. It is important for 3D shape understanding…
Multidimensional Byte Pair Encoding: Shortened Sequences for Improved Visual Data Generation
Tim Elsner, Paula Usinger, Julius Nehring-Wirxel +5
In language processing, transformers benefit greatly from text being condensed. This is achieved through a larger vocabulary that captures word fragments instead of plain character…
Quantised Global Autoencoder: A Holistic Approach to Representing Visual Data
Tim Elsner, Paula Usinger, Victor Czech +4
In quantised autoencoders, images are usually split into local patches, each encoded by one token. This representation is redundant in the sense that the same number of tokens is s…
Retargeting Visual Data with Deformation Fields
Tim Elsner, Julia Berger, Tong Wu +3
Seam carving is an image editing method that enable content-aware resizing, including operations like removing objects. However, the seam-finding strategy based on dynamic programm…
Adaptive Voronoi NeRFs
Tim Elsner, Victor Czech, Julia Berger +3
Neural Radiance Fields (NeRFs) learn to represent a 3D scene from just a set of registered images. Increasing sizes of a scene demands more complex functions, typically represented…
Intuitive Shape Editing in Latent Space
Tim Elsner, Moritz Ibing, Victor Czech +2
The use of autoencoders for shape editing or generation through latent space manipulation suffers from unpredictable changes in the output shape. Our autoencoder-based method enabl…
Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
Laurent Kloeker, Fabian Thomsen, Lutz Eckstein +6
The research project HDV-Mess aims at a currently missing, but very crucial component for addressing important challenges in the field of connected and automated driving on public…