Thanh Le — accepted AI-conference papers

2026

Verifying Neural Network Robustness with Dual Perturbations

Hai Duong, Lam Nguyen, Thanh Le, ThanhVu Nguyen

CVPR 2026

Safety-critical deep learning systems must be robust against real-world corruptions combining spatially correlated distortions and independent noise.Current deep neural network verification methods handle these perturbations separately, either checking independent pixel-wise perturbations or restric

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2023

PlanarTrack: A Large-scale Challenging Benchmark for Planar Object Tracking

Xinran Liu, Xiaoqiong Liu, Ziruo Yi, Xin Zhou, Thanh Le, Libo Zhang +3

ICCV 2023poster

Planar object tracking is a critical computer vision problem and has drawn increasing interest owing to its key roles in robotics, augmented reality, etc. Despite rapid progress, its further development, especially in the deep learning era, is largely hindered due to the lack of large-scale challeng…

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