35 citations · 144 across the 16 of their papers we have counts for
16 papers
Coupled Video Frame Interpolation and Encoding with Hybrid Event Cameras for Low-Power High-Framerate Video
Hidekazu Takahashi, Takefumi Nagumo, Kensei Jo +6
Every generation of mobile devices strives to capture video at higher resolution and frame rate than previous ones. This quality increase also requires additional power and computa…
Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
Bingxin Ke, Anton Obukhov, Shengyu Huang +3
Monocular depth estimation is a fundamental computer vision task. Recovering 3D depth from a single image is geometrically ill-posed and requires scene understanding, so it is not…
Thera: Aliasing-Free Arbitrary-Scale Super-Resolution with Neural Heat Fields
Alexander Becker, Rodrigo Caye Daudt, Dominik Narnhofer +4
Recent approaches to arbitrary-scale single image super-resolution (ASR) use neural fields to represent continuous signals that can be sampled at arbitrary resolutions. However, po…
High-resolution Population Maps Derived from Sentinel-1 and Sentinel-2
Nando Metzger, Rodrigo Caye Daudt, Devis Tuia +1
Detailed population maps play an important role in diverse fields ranging from humanitarian action to urban planning. Generating such maps in a timely and scalable manner presents…
Fine-grained Population Mapping from Coarse Census Counts and Open Geodata
Nando Metzger, John E. Vargas-Muñoz, Rodrigo C. Daudt +6
Fine-grained population maps are needed in several domains, like urban planning, environmental monitoring, public health, and humanitarian operations. Unfortunately, in many countr…
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…
Guided Depth Super-Resolution by Deep Anisotropic Diffusion
Nando Metzger, Rodrigo Caye Daudt, Konrad Schindler
Performing super-resolution of a depth image using the guidance from an RGB image is a problem that concerns several fields, such as robotics, medical imaging, and remote sensing.…
Satellite-based high-resolution maps of cocoa planted area for Côte d'Ivoire and Ghana
Nikolai Kalischek, Nico Lang, Cécile Renier +7
Côte d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, prov…
Recognition of Unseen Bird Species by Learning from Field Guides
Andrés C. Rodríguez, Stefano D'Aronco, Rodrigo Caye Daudt +2
We exploit field guides to learn bird species recognition, in particular zero-shot recognition of unseen species. Illustrations contained in field guides deliberately focus on disc…
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation
Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz +6
The ability to estimate epistemic uncertainty is often crucial when deploying machine learning in the real world, but modern methods often produce overconfident, uncalibrated uncer…
Weakly Supervised Change Detection Using Guided Anisotropic Difusion
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch +1
Large scale datasets created from crowdsourced labels or openly available data have become crucial to provide training data for large scale learning algorithms. While these dataset…
Mapping Vulnerable Populations with AI
Benjamin Kellenberger, John E. Vargas-Muñoz, Devis Tuia +6
Humanitarian actions require accurate information to efficiently delegate support operations. Such information can be maps of building footprints, building functions, and populatio…
Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch +1
Large scale datasets created from user labels or openly available data have become crucial to provide training data for large scale learning algorithms. While these datasets are ea…
Urban Change Detection for Multispectral Earth Observation Using Convolutional Neural Networks
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch +1
The Copernicus Sentinel-2 program now provides multispectral images at a global scale with a high revisit rate. In this paper we explore the usage of convolutional neural networks…
Fully Convolutional Siamese Networks for Change Detection
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch
This paper presents three fully convolutional neural network architectures which perform change detection using a pair of coregistered images. Most notably, we propose two Siamese…
Multitask Learning for Large-scale Semantic Change Detection
Rodrigo Caye Daudt, Bertrand Le Saux, Alexandre Boulch +1
Change detection is one of the main problems in remote sensing, and is essential to the accurate processing and understanding of the large scale Earth observation data available th…