activity
20202026
most citedAdjusting Bias in Long Range Stereo Matching: A semantics guided approach

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

RMR-P: Road Metadata-Aware Restoration for Pavement Inspection

Amir Ghorbani, Amirali K. Gostar, WeiQin Chuah +4

Road-surface images captured by vehicle-mounted cameras are often degraded by motion blur, defocus, poor illumination, and noise due to vehicle motion, camera limitations, and vary…

cs.CV2024

Enhanced Online Test-time Adaptation with Feature-Weight Cosine Alignment

WeiQin Chuah, Ruwan Tennakoon, Alireza Bab-Hadiashar

Online Test-Time Adaptation (OTTA) has emerged as an effective strategy to handle distributional shifts, allowing on-the-fly adaptation of pre-trained models to new target domains…

cs.CV2023

Single Domain Generalization via Normalised Cross-correlation Based Convolutions

WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2

Deep learning techniques often perform poorly in the presence of domain shift, where the test data follows a different distribution than the training data. The most practically des…

cs.CV2022

ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks

WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2

State-of-the-art stereo matching networks trained only on synthetic data often fail to generalize to more challenging real data domains. In this paper, we attempt to unfold an impo…

cs.CV2020★ 3 cited

Adjusting Bias in Long Range Stereo Matching: A semantics guided approach

WeiQin Chuah, Ruwan Tennakoon, Reza Hoseinnezhad +2

Stereo vision generally involves the computation of pixel correspondences and estimation of disparities between rectified image pairs. In many applications, including simultaneous…