4 papers
VisAdj: Learning Adjacency Matrices from Node-Link Images
Jiahao Xie, Guangmo Tong
Learning adjacency matrices from node-link images is a fundamental problem for recovering structured graph information from visual observations. Existing methods typically rely on…
VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection
Jiahao Xie, Guangmo Tong
Graph property detection aims to determine whether a graph exhibits certain structural properties, such as being Hamiltonian. Recently, learning-based approaches have shown great p…
CNS-Bench: Benchmarking Image Classifier Robustness Under Continuous Nuisance Shifts
Olaf Dünkel, Artur Jesslen, Jiahao Xie +3
An important challenge when using computer vision models in the real world is to evaluate their performance in potential out-of-distribution (OOD) scenarios. While simple synthetic…
Test-Time Visual In-Context Tuning
Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr +2
Visual in-context learning (VICL), as a new paradigm in computer vision, allows the model to rapidly adapt to various tasks with only a handful of prompts and examples. While effec…