10 citations · 21 across the 10 of their papers we have counts for
7 papers · 1 filter
GeoSceneGraph: Geometric Scene Graph Diffusion Model for Text-guided 3D Indoor Scene Synthesis
Antonio Ruiz, Tao Wu, Andrew Melnik +6
Methods that synthesize indoor 3D scenes from text prompts have wide-ranging applications in film production, interior design, video games, virtual reality, and synthetic data gene…
Lane Graph Extraction from Aerial Imagery via Lane Segmentation Refinement with Diffusion Models
Antonio Ruiz, Andrew Melnik, Nicolo Savioli +3
The lane graph is critical for applications such as autonomous driving and lane-level route planning. While previous research has focused on extracting lane-level graphs from aeria…
Shape complexity estimation using VAE
Markus Rothgaenger, Andrew Melnik, Helge Ritter
In this paper, we compare methods for estimating the complexity of two-dimensional shapes and introduce a method that exploits reconstruction loss of Variational Autoencoders with…
Stroke-based Rendering: From Heuristics to Deep Learning
Florian Nolte, Andrew Melnik, Helge Ritter
In the last few years, artistic image-making with deep learning models has gained a considerable amount of traction. A large number of these models operate directly in the pixel sp…
Faces: AI Blitz XIII Solutions
Andrew Melnik, Eren Akbulut, Jannik Sheikh +3
AI Blitz XIII Faces challenge hosted on www.aicrowd.com platform consisted of five problems: Sentiment Classification, Age Prediction, Mask Prediction, Face Recognition, and Face D…
YOLO -- You only look 10647 times
Christian Limberg, Andrew Melnik, Augustin Harter +1
With this work we are explaining the "You Only Look Once" (YOLO) single-stage object detection approach as a parallel classification of 10647 fixed region proposals. We support thi…