3 citations · 4 across the 5 of their papers we have counts for
9 papers
The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2
Olivier Dietrich, Merlin Alfredsson, Emilia Arens +5
Natural disasters demand rapid damage assessment to guide humanitarian response. Here, we investigate whether medium-resolution Earth observation images from the Copernicus program…
Video Depth without Video Models
Bingxin Ke, Dominik Narnhofer, Shengyu Huang +5
Video depth estimation lifts monocular video clips to 3D by inferring dense depth at every frame. Recent advances in single-image depth estimation, brought about by the rise of lar…
AGBD: A Global-scale Biomass Dataset
Ghjulia Sialelli, Torben Peters, Jan D. Wegner +1
Accurate estimates of Above Ground Biomass (AGB) are essential in addressing two of humanity's biggest challenges: climate change and biodiversity loss. Existing datasets for AGB e…
An Open-Source Tool for Mapping War Destruction at Scale in Ukraine using Sentinel-1 Time Series
Olivier Dietrich, Torben Peters, Vivien Sainte Fare Garnot +4
Access to detailed war impact assessments is crucial for humanitarian organizations to assist affected populations effectively. However, maintaining a comprehensive understanding o…
Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning
Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni +4
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver…
Towards accurate instance segmentation in large-scale LiDAR point clouds
Binbin Xiang, Torben Peters, Theodora Kontogianni +4
Panoptic segmentation is the combination of semantic and instance segmentation: assign the points in a 3D point cloud to semantic categories and partition them into distinct object…
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds
Binbin Xiang, Yuanwen Yue, Torben Peters +1
3D point cloud panoptic segmentation is the combined task to (i) assign each point to a semantic class and (ii) separate the points in each class into object instances. Recently th…
TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generation
Nikolai Kalischek, Torben Peters, Jan D. Wegner +1
Probabilistic denoising diffusion models (DDMs) have set a new standard for 2D image generation. Extending DDMs for 3D content creation is an active field of research. Here, we pro…
BiasBed -- Rigorous Texture Bias Evaluation
Nikolai Kalischek, Rodrigo C. Daudt, Torben Peters +3
The well-documented presence of texture bias in modern convolutional neural networks has led to a plethora of algorithms that promote an emphasis on shape cues, often to support ge…