7 papers
Learning to Predict Repeatability of Interest Points
Anh-Dzung Doan, Daniyar Turmukhambetov, Yasir Latif +2
Many robotics applications require interest points that are highly repeatable under varying viewpoints and lighting conditions. However, this requirement is very challenging as the…
HM4: Hidden Markov Model with Memory Management for Visual Place Recognition
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +1
Visual place recognition needs to be robust against appearance variability due to natural and man-made causes. Training data collection should thus be an ongoing process to allow c…
In defense of OSVOS
Yu Liu, Yutong Dai, Anh-Dzung Doan +2
As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regardi…
Scalable Place Recognition Under Appearance Change for Autonomous Driving
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +3
A major challenge in place recognition for autonomous driving is to be robust against appearance changes due to short-term (e.g., weather, lighting) and long-term (seasons, vegetat…
Visual Localization Under Appearance Change: Filtering Approaches
Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin +4
A major focus of current research on place recognition is visual localization for autonomous driving. In this scenario, as cameras will be operating continuously, it is realistic t…
G2D: from GTA to Data
Anh-Dzung Doan, Abdul Mohsi Jawaid, Thanh-Toan Do +1
This document describes G2D, a software that enables capturing videos from Grand Theft Auto V (GTA V), a popular role playing game set in an expansive virtual city. The target user…