6 papers
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…
Category Level 6D Object Pose Estimation from a Single RGB Image using Diffusion
Adam Bethell, Ravi Garg, Ian Reid
Estimating the 6D pose and 3D size of an object from visual data is a fundamental task in computer vision. Although single-view geometry is a deeply established domain, contemporar…
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…
What Images are More Memorable to Machines?
Junlin Han, Huangying Zhan, Jie Hong +4
This paper studies the problem of measuring and predicting how memorable an image is to pattern recognition machines, as a path to explore machine intelligence. Firstly, we propose…