1 citations · 1 across the 8 of their papers we have counts for
8 papers
Guided Super-Resolution of Digital Elevation Models with Diffusion-Based Image Generators
Armand Mihai Nicolicioiu, Dominik Narnhofer, Nando Metzger +3
High-resolution digital surface models (DSMs) play an important role in urban analysis, 3D building reconstruction, and infrastructure monitoring, yet their availability remains li…
Diffusion Transformers for Roof Graph Synthesis and Reconstruction
Daniel Panangian, Ksenia Bittner
We present RoofDiT, a generative framework for 2D roof graph synthesis and reconstruction. Roofs are compactly described as planar graphs of junctions and structural edges, but exi…
AIM2PC: Aerial Image to 3D Building Point Cloud Reconstruction
Soulaimene Turki, Daniel Panangian, Houda Chaabouni-Chouayakh +1
Three-dimensional urban reconstruction of buildings from single-view images has attracted significant attention over the past two decades. However, recent methods primarily focus o…
PolyRoof: Precision Roof Polygonization in Urban Residential Building with Graph Neural Networks
Chaikal Amrullah, Daniel Panangian, Ksenia Bittner
The growing demand for detailed building roof data has driven the development of automated extraction methods to overcome the inefficiencies of traditional approaches, particularly…
Dfilled: Repurposing Edge-Enhancing Diffusion for Guided DSM Void Filling
Daniel Panangian, Ksenia Bittner
Digital Surface Models (DSMs) are essential for accurately representing Earth's topography in geospatial analyses. DSMs capture detailed elevations of natural and manmade features,…
Can Location Embeddings Enhance Super-Resolution of Satellite Imagery?
Daniel Panangian, Ksenia Bittner
Publicly available satellite imagery, such as Sentinel- 2, often lacks the spatial resolution required for accurate analysis of remote sensing tasks including urban planning and di…
SyntStereo2Real: Edge-Aware GAN for Remote Sensing Image-to-Image Translation while Maintaining Stereo Constraint
Vasudha Venkatesan, Daniel Panangian, Mario Fuentes Reyes +1
In the field of remote sensing, the scarcity of stereo-matched and particularly lack of accurate ground truth data often hinders the training of deep neural networks. The use of sy…
Real-GDSR: Real-World Guided DSM Super-Resolution via Edge-Enhancing Residual Network
Daniel Panangian, Ksenia Bittner
A low-resolution digital surface model (DSM) features distinctive attributes impacted by noise, sensor limitations and data acquisition conditions, which failed to be replicated us…