3.5k citations · 3.6k across the 12 of their papers we have counts for
16 papers
Globally Optimal Event-Based Divergence Estimation for Ventral Landing
Sofia McLeod, Gabriele Meoni, Dario Izzo +5
Event sensing is a major component in bio-inspired flight guidance and control systems. We explore the usage of event cameras for predicting time-to-contact (TTC) with the surface…
Towards Bridging the Space Domain Gap for Satellite Pose Estimation using Event Sensing
Mohsi Jawaid, Ethan Elms, Yasir Latif +1
Deep models trained using synthetic data require domain adaptation to bridge the gap between the simulation and target environments. State-of-the-art domain adaptation methods ofte…
Asynchronous Optimisation for Event-based Visual Odometry
Daqi Liu, Alvaro Parra, Yasir Latif +3
Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range. On the other hand, developing effective event-based vision algorithm…
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…
Monocular Rotational Odometry with Incremental Rotation Averaging and Loop Closure
Chee-Kheng Chng, Alvaro Parra, Tat-Jun Chin +1
Estimating absolute camera orientations is essential for attitude estimation tasks. An established approach is to first carry out visual odometry (VO) or visual SLAM (V-SLAM), and…
Improved Visual Localization via Graph Smoothing
Carlos Lassance, Yasir Latif, Ravi Garg +2
Vision based localization is the problem of inferring the pose of the camera given a single image. One solution to this problem is to learn a deep neural network to infer the pose…
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…
Real-Time Monocular Object-Model Aware Sparse SLAM
Mehdi Hosseinzadeh, Kejie Li, Yasir Latif +1
Simultaneous Localization And Mapping (SLAM) is a fundamental problem in mobile robotics. While sparse point-based SLAM methods provide accurate camera localization, the generated…
Structure Aware SLAM using Quadrics and Planes
Mehdi Hosseinzadeh, Yasir Latif, Trung Pham +2
Simultaneous Localization And Mapping (SLAM) is a fundamental problem in mobile robotics. While point-based SLAM methods provide accurate camera localization, the generated maps la…
Learning Deeply Supervised Good Features to Match for Dense Monocular Reconstruction
Chamara Saroj Weerasekera, Ravi Garg, Yasir Latif +1
Visual SLAM (Simultaneous Localization and Mapping) methods typically rely on handcrafted visual features or raw RGB values for establishing correspondences between images. These f…
Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks
Yasir Latif, Ravi Garg, Michael Milford +1
Place recognition is an essential component of Simultaneous Localization And Mapping (SLAM). Under severe appearance change, reliable place recognition is a difficult perception ta…
Sparse Optimization for Robust and Efficient Loop Closing
Yasir Latif, Guoquan Huang, John Leonard +1
It is essential for a robot to be able to detect revisits or loop closures for long-term visual navigation.A key insight explored in this work is that the loop-closing event inhere…
Meaningful Maps With Object-Oriented Semantic Mapping
Niko Sünderhauf, Trung T. Pham, Yasir Latif +2
For intelligent robots to interact in meaningful ways with their environment, they must understand both the geometric and semantic properties of the scene surrounding them. The maj…
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Cesar Cadena, Luca Carlone, Henry Carrillo +5
Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving wit…