7 papers
Robust PnP on a Neuromorphic Processor for Object Pose Estimation
Tam Ngoc-Bang Nguyen, Mohsi Jawaid, Tat-Jun Chin
Neuromorphic computing is gaining attention in robotic perception due to its higher energy efficiency. While neural network-based methods can more readily exploit the distributed a…
Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes
Ryan Faulkner, Luke Haub, Simon Ratcliffe +1
LiDAR scanning in outdoor scenes acquires accurate distance measurements over wide areas, producing large-scale point clouds. Application examples for this data include robotics, a…
Event-driven Robust Fitting on Neuromorphic Hardware
Tam Ngoc-Bang Nguyen, Anh-Dzung Doan, Zhipeng Cai +1
Robust fitting of geometric models is a fundamental task in many computer vision pipelines. Numerous innovations have been produced on the topic, from improving the efficiency and…
Simultaneous Diffusion Sampling for Conditional LiDAR Generation
Ryan Faulkner, Luke Haub, Simon Ratcliffe +3
By enabling capturing of 3D point clouds that reflect the geometry of the immediate environment, LiDAR has emerged as a primary sensor for autonomous systems. If a LiDAR scan is to…
TC-PDM: Temporally Consistent Patch Diffusion Models for Infrared-to-Visible Video Translation
Anh-Dzung Doan, Vu Minh Hieu Phan, Surabhi Gupta +3
Infrared imaging offers resilience against changing lighting conditions by capturing object temperatures. Yet, in few scenarios, its lack of visual details compared to daytime visi…
Weakly Supervised Test-Time Domain Adaptation for Object Detection
Anh-Dzung Doan, Bach Long Nguyen, Terry Lim +6
Prior to deployment, an object detector is trained on a dataset compiled from a previous data collection campaign. However, the environment in which the object detector is deployed…
Domain Adaptation for Satellite-Borne Hyperspectral Cloud Detection
Andrew Du, Anh-Dzung Doan, Yee Wei Law +1
The advent of satellite-borne machine learning hardware accelerators has enabled the on-board processing of payload data using machine learning techniques such as convolutional neu…