3 papers
cs.CV2026
D-GAP: Improving Out-of-Domain Robustness via Dataset-Agnostic and Gradient-Guided Augmentation in Frequency and Pixel Spaces
Ruoqi Wang, Haitao Wang, Shaojie Guo +1
Out-of-domain (OOD) robustness is challenging to achieve in real-world computer vision applications, where shifts in image background, style, and acquisition instruments always deg…
cs.CV2025
GalaxAlign: Mimicking Citizen Scientists' Multimodal Guidance for Galaxy Morphology Analysis
Ruoqi Wang, Haitao Wang, Qiong Luo
Galaxy morphology analysis involves studying galaxies based on their shapes and structures. For such studies, fundamental tasks include identifying and classifying galaxies in astr…
cs.CV2025
Improving Out-of-Domain Robustness with Targeted Augmentation in Frequency and Pixel Spaces
Ruoqi Wang, Haitao Wang, Shaojie Guo +1
Out-of-domain (OOD) robustness under domain adaptation settings, where labeled source data and unlabeled target data come from different distributions, is a key challenge in real-w…