activity
20172026
most citedA graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery

7 citations · 28 across the 37 of their papers we have counts for

collaborators
Showing 2025Show all

19 papers · 1 filter

cs.CV2025

DNA-Prior: Unsupervised Denoise Anything via Dual-Domain Prior

Yanqi Cheng, Chun-Wun Cheng, Jim Denholm +5

Medical imaging pipelines critically rely on robust denoising to stabilise downstream tasks such as segmentation and reconstruction. However, many existing denoisers depend on larg…

cs.LG2025

PDE Solvers Should Be Local: Fast, Stable Rollouts with Learned Local Stencils

Chun-Wun Cheng, Bin Dong, Carola-Bibiane Schönlieb +1

Neural operator models for solving partial differential equations (PDEs) often rely on global mixing mechanisms-such as spectral convolutions or attention-which tend to oversmooth…

cs.LG2025

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows

Moshe Eliasof, Eldad Haber, Carola-Bibiane Schönlieb

We introduce TANGO -- a dynamical systems inspired framework for graph representation learning that governs node feature evolution through a learned energy landscape and its associ…

eess.IV2025

PhotIQA: A photoacoustic image data set with image quality ratings

Anna Breger, Janek Gröhl, Clemens Karner +7

Image quality assessment (IQA) is crucial in the evaluation stage of novel algorithms operating on images, including traditional and machine learning based methods. Due to the lack…

cs.CV2025

Bridging Annotation Gaps: Transferring Labels to Align Object Detection Datasets

Mikhail Kennerley, Angelica Aviles-Rivero, Carola-Bibiane Schönlieb +1

Combining multiple object detection datasets offers a path to improved generalisation but is hindered by inconsistencies in class semantics and bounding box annotations. Some metho…

cs.LG2025

Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks

Ali Hariri, Álvaro Arroyo, Alessio Gravina +6

ChebNet, one of the earliest spectral GNNs, has largely been overshadowed by Message Passing Neural Networks (MPNNs), which gained popularity for their simplicity and effectiveness…