Search Results - "Object Detection, Segmentation and Categorization"

On Onboard LiDAR-Based Flying Object Detection by Vrba, Matous, Walter, Viktor, Pritzl, Vaclav, Pliska, Michal, Baca, Tomas, Spurny, Vojtech, Hert, Daniel, Saska, Martin

“…A new robust and accurate approach for the detection and localization of flying objects with the purpose of highly dynamic aerial interception and agile…”
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Focal Loss in 3D Object Detection by Yun, Peng, Tai, Lei, Wang, Yuan, Liu, Chengju, Liu, Ming

“…3D object detection is still an open problem in autonomous driving scenes. When recognizing and localizing key objects from sparse 3D inputs, autonomous…”
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Emperror: A Flexible Generative Perception Error Model for Probing Self-Driving Planners by Hanselmann, Niklas, Doll, Simon, Cordts, Marius, Lensch, Hendrik P.A., Geiger, Andreas

“…To handle the complexities of real-world traffic, learning planners for self-driving from data is a promising direction. While recent approaches have shown…”
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Intensity Image-Based LiDAR Fiducial Marker System by Liu, Yibo, Schofield, Hunter, Shan, Jinjun

“…The fiducial marker system for LiDAR is crucial for the robotic application but it is still rare to date. In this letter, an Intensity Image-based LiDAR…”
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A Bayesian Modeling Framework for Estimation and Ground Segmentation of Cluttered Staircases by Sriganesh, Prasanna, Shirose, Burhanuddin, Travers, Matthew

“…Autonomous robot navigation in complex environments requires robust perception as well as high-level scene understanding due to perceptual challenges, such as…”
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Generalizable Stable Points Segmentation for 3D LiDAR Scan-to-Map Long-Term Localization by Hroob, Ibrahim, Mersch, Benedikt, Stachniss, Cyrill, Hanheide, Marc

“…Mobile robots increasingly operate in real-world environments that are subject to change over time. Accurate and robust localization is, however, crucial for…”
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SPLASH-SegFormer Pipeline: A Transformer-Based Approach for High-Resolution and Low-Cost Laser Scanner Seafloor Mapping by Fuentes-Guinez, Javiera, Troni, Giancarlo, Lobel, Hans

“…High-resolution seafloor mapping continues to be challenging, primarily due to the high costs and complexity of traditional sensors. Laser scanners offer a…”
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Co-Fix3D: Enhancing 3D Object Detection With Collaborative Refinement by Li, Wenxuan, Zou, Qin, Chen, Chi, Du, Bo, Chen, Long, Zhou, Jian, Yu, Hongkai

“…3D object detection in driving scenarios is particularly challenging due to factors such as sensor noise, occlusions, and the inherent sparsity of LiDAR point…”
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Interactive Robotic Moving Cable Segmentation by Motion Correlation by Holesovsky, Ondrej, Skoviera, Radoslav, Hlavac, Vaclav

“…Manipulating tangled hoses, cables, or ropes can be challenging for both robots and humans. Humans often approach these perceptually demanding tasks by pushing…”
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BEVCon: Advancing Bird's Eye View Perception with Contrastive Learning by Leng, Ziyang, Yang, Jiawei, Ren, Zhicheng, Zhou, Bolei

“…We present BEVCon, a simple yet effective contrastive learning framework designed to improve Bird's Eye View (BEV) perception in autonomous driving. BEV…”
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Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation by Opipari, Anthony, Krishnan, Aravindhan K, Gayaka, Shreekant, Sun, Min, Kuo, Cheng-Hao, Sen, Arnie, Jenkins, Odest Chadwicke

“…This letter presents a method for generating large-scale datasets to improve class-agnostic video segmentation across robots with different form factors…”
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Non-Contact Tactile Perception for Hybrid-Active Gripper by Pereira, Jonathas H. M., Joventino, Carlos F., Fabro, Joao A., de Oliveira, Andre S.

“…This letter presents a novel approach to object recognition using a reconfigurable gripper with multiple time-of-flight (ToF) sensors attached to the fingers…”
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Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection by Mouawad, Issa, Brasch, Nikolas, Manhardt, Fabian, Tombari, Federico, Odone, Francesca

“…Monocular 3D object detection continues to attract attention due to the cost benefits and wider availability of RGB cameras. Despite the recent advances and…”
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