59 citations · 150 across the 8 of their papers we have counts for
14 papers
SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections
Mark Boss, Andreas Engelhardt, Abhishek Kar +5
Inverse rendering of an object under entirely unknown capture conditions is a fundamental challenge in computer vision and graphics. Neural approaches such as NeRF have achieved ph…
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
Leonard Salewski, A. Sophia Koepke, Hendrik P. A. Lensch +1
Providing explanations in the context of Visual Question Answering (VQA) presents a fundamental problem in machine learning. To obtain detailed insights into the process of generat…
Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition
Mark Boss, Varun Jampani, Raphael Braun +3
Decomposing a scene into its shape, reflectance and illumination is a fundamental problem in computer vision and graphics. Neural approaches such as NeRF have achieved remarkable s…
Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task Training
Hassan Shahmohammadi, Hendrik P. A. Lensch, R. Harald Baayen
Language grounding aims at linking the symbolic representation of language (e.g., words) into the rich perceptual knowledge of the outside world. The general approach is to embed b…
NeRD: Neural Reflectance Decomposition from Image Collections
Mark Boss, Raphael Braun, Varun Jampani +3
Decomposing a scene into its shape, reflectance, and illumination is a challenging but important problem in computer vision and graphics. This problem is inherently more challengin…
Learning to Adapt Multi-View Stereo by Self-Supervision
Arijit Mallick, Jörg Stückler, Hendrik Lensch
3D scene reconstruction from multiple views is an important classical problem in computer vision. Deep learning based approaches have recently demonstrated impressive reconstructio…