38 citations · 104 across the 12 of their papers we have counts for
14 papers · 1 filter
Video Depth Propagation
Luigi Piccinelli, Thiemo Wandel, Christos Sakaridis +2
Depth estimation in videos is essential for visual perception in real-world applications. However, existing methods either rely on simple frame-by-frame monocular models, leading t…
DGFusion: Depth-Guided Sensor Fusion for Robust Semantic Perception
Tim Broedermannn, Christos Sakaridis, Luigi Piccinelli +2
Robust semantic perception for autonomous vehicles relies on effectively combining multiple sensors with complementary strengths and weaknesses. State-of-the-art sensor fusion appr…
UniK3D: Universal Camera Monocular 3D Estimation
Luigi Piccinelli, Christos Sakaridis, Mattia Segu +4
Monocular 3D estimation is crucial for visual perception. However, current methods fall short by relying on oversimplified assumptions, such as pinhole camera models or rectified i…
UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler
Luigi Piccinelli, Christos Sakaridis, Yung-Hsu Yang +4
Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of recent MMDE methods is c…
MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation
Jonas Heylen, Mark De Wolf, Bruno Dawagne +5
Monocular 3D object detection has recently shown promising results, however there remain challenging problems. One of those is the lack of invariance to different camera intrinsic…
ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception
Christos Sakaridis, Haoran Wang, Ke Li +6
Level-5 driving automation requires a robust visual perception system that can parse input images under any condition. However, existing driving datasets for dense semantic percept…
3D Object Discovery and Modeling Using Single RGB-D Images Containing Multiple Object Instances
Wim Abbeloos, Esra Ataer-Cansizoglu, Sergio Caccamo +2
Unsupervised object modeling is important in robotics, especially for handling a large set of objects. We present a method for unsupervised 3D object discovery, reconstruction, and…
Detecting and Grouping Identical Objects for Region Proposal and Classification
Wim Abbeloos, Sergio Caccamo, Esra Ataer-Cansizoglu +3
Often multiple instances of an object occur in the same scene, for example in a warehouse. Unsupervised multi-instance object discovery algorithms are able to detect and identify s…
Team Applied Robotics: A closer look at our robotic picking system
Wim Abbeloos, Fabian Gouwens, Simon Jansen +3
This paper describes the vision based robotic picking system that was developed by our team, Team Applied Robotics, for the Amazon Picking Challenge 2016. This competition challeng…
Exploring the potential of combining time of flight and thermal infrared cameras for person detection
Wim Abbeloos, Toon Goedemé
Combining new, low-cost thermal infrared and time-of-flight range sensors provides new opportunities. In this position paper we explore the possibilities of combining these sensors…
Process Monitoring of Extrusion Based 3D Printing via Laser Scanning
Matthias Faes, Wim Abbeloos, Frederik Vogeler +4
Extrusion based 3D Printing (E3DP) is an Additive Manufacturing (AM) technique that extrudes thermoplastic polymer in order to build up components using a layerwise approach. Hereb…
Embedded Line Scan Image Sensors: The Low Cost Alternative for High Speed Imaging
Stef Van Wolputte, Wim Abbeloos, Stijn Helsen +2
In this paper we propose a low-cost high-speed imaging line scan system. We replace an expensive industrial line scan camera and illumination with a custom-built set-up of cheap of…
Fusion of Range and Thermal Images for Person Detection
Wim Abbeloos, Toon Goedemé
Detecting people in images is a challenging problem. Differences in pose, clothing and lighting, along with other factors, cause a lot of variation in their appearance. To overcome…
Point Pair Feature based Object Detection for Random Bin Picking
Wim Abbeloos, Toon Goedemé
Point pair features are a popular representation for free form 3D object detection and pose estimation. In this paper, their performance in an industrial random bin picking context…