7 citations · 12 across the 5 of their papers we have counts for
5 papers
Momentum-Conserving Graph Neural Networks for Deformable Objects
Jiahong Wang, Logan Numerow, Stelian Coros +3
Graph neural networks (GNNs) have emerged as a versatile and efficient option for modeling the dynamic behavior of deformable materials. While GNNs generalize readily to arbitrary…
IntrinsicEdit: Precise generative image manipulation in intrinsic space
Linjie Lyu, Valentin Deschaintre, Yannick Hold-Geoffroy +5
Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack prec…
Learning Images Across Scales Using Adversarial Training
Krzysztof Wolski, Adarsh Djeacoumar, Alireza Javanmardi +7
The real world exhibits rich structure and detail across many scales of observation. It is difficult, however, to capture and represent a broad spectrum of scales using ordinary im…
Neural Gaussian Scale-Space Fields
Felix Mujkanovic, Ntumba Elie Nsampi, Christian Theobalt +2
Gaussian scale spaces are a cornerstone of signal representation and processing, with applications in filtering, multiscale analysis, anti-aliasing, and many more. However, obtaini…
PIE: Portrait Image Embedding for Semantic Control
Ayush Tewari, Mohamed Elgharib, Mallikarjun B R. +5
Editing of portrait images is a very popular and important research topic with a large variety of applications. For ease of use, control should be provided via a semantically meani…