138 citations · 263 across the 9 of their papers we have counts for
12 papers
Li3DeTr: A LiDAR based 3D Detection Transformer
Gopi Krishna Erabati, Helder Araujo
Inspired by recent advances in vision transformers for object detection, we propose Li3DeTr, an end-to-end LiDAR based 3D Detection Transformer for autonomous driving, that inputs…
MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving
Gopi Krishna Erabati, Helder Araujo
3D object detection is a significant task for autonomous driving. Recently with the progress of vision transformers, the 2D object detection problem is being treated with the set-t…
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner
Kutsev Bengisu Ozyoruk, Guliz Irem Gokceler, Gulfize Coskun +12
Deep learning techniques hold promise to develop dense topography reconstruction and pose estimation methods for endoscopic videos. However, currently available datasets do not sup…
Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Evin Pinar Ornek +3
Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging…
EndoSensorFusion: Particle Filtering-Based Multi-sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots
Mehmet Turan, Yasin Almalioglu, Hunter Gilbert +3
A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagn…
3D Reconstruction with Low Resolution, Small Baseline and High Radial Distortion Stereo Images
Tiago Dias, Helder Araujo, Pedro Miraldo
In this paper we analyze and compare approaches for 3D reconstruction from low-resolution (250x250), high radial distortion stereo images, which are acquired with small baseline (a…