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CAR: Class-aware Regularizations for Semantic Segmentation [article]

Ye Huang, Di Kang, Liang Chen, Xuefei Zhe, Wenjing Jia, Xiangjian He, Linchao Bao
2022 arXiv   pre-print
In this paper, aiming to use class level information more effectively, we propose a universal Class-Aware Regularization (CAR) approach to optimize the intra-class variance and inter-class distance during  ...  Recent segmentation methods, such as OCR and CPNet, utilizing "class level" information in addition to pixel features, have achieved notable success for boosting the accuracy of existing network modules  ...  Introduction Semantic segmentation, which assigns a class label for each pixel in an image, is a fundamental task in computer vision.  ... 
arXiv:2203.07160v2 fatcat:jkzfce3tfbgjtgao5rzqqhm7na

PCSCNet: Fast 3D Semantic Segmentation of LiDAR Point Cloud for Autonomous Car using Point Convolution and Sparse Convolution Network [article]

Jaehyun Park, Chansoo Kim, Kichun Jo
2022 arXiv   pre-print
The autonomous car must recognize the driving environment quickly for safe driving.  ...  As the Light Detection And Range (LiDAR) sensor is widely used in the autonomous car, fast semantic segmentation of LiDAR point cloud, which is the point-wise classification of the point cloud within the  ...  As you can see, our model well classifies car, terrain, building, and road classes. Especially, the points from car class are segmented well with our model.  ... 
arXiv:2202.10047v1 fatcat:slrwq7hhy5axriublzp7x6i5wy

Fast car detection using image strip features

Wei Zheng, Luhong Liang
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
This paper presents a fast method for detecting multi-view cars in real-world scenes.  ...  Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features.  ...  For example, eyes are always darker than skin of cheeks, but there is no such simple regularity between cars and background.  ... 
doi:10.1109/cvpr.2009.5206642 dblp:conf/cvpr/ZhengL09 fatcat:u232g37ilfbdrcdaqdajwftlb4

Fast car detection using image strip features

Wei Zheng, Luhong Liang
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
This paper presents a fast method for detecting multi-view cars in real-world scenes.  ...  Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features.  ...  For example, eyes are always darker than skin of cheeks, but there is no such simple regularity between cars and background.  ... 
doi:10.1109/cvprw.2009.5206642 fatcat:fcqy72yggze4tdgbjnwq4oz6uu

Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation [article]

Rakshith Shetty and Bernt Schiele and Mario Fritz
2018 arXiv   pre-print
We apply this methodology on two tasks, image classification and semantic segmentation, and discover undesirable dependency between objects and context, for example that "sidewalk" segmentation relies  ...  However, to what extent the computer vision models for image classification and semantic segmentation are dependent on the context to make their predictions is unclear.  ...  For example, in our experiments we find that keyboard is often not recognized without a nearby monitor, and semantic segmentation of roads suffers without cars (see Figure 1 ).  ... 
arXiv:1812.06707v1 fatcat:qzwduwefgneodfxrx3y4k7sp5i

Semantic-based operators to support car sketching

V. Cheutet, C. E. Catalano, F. Giannini, M. Monti, B. Falcidieno, J. C. Leon
2007 Journal of engineering design  
Key action: 2.3.1.7 Semantic-based  ...  Acknowledgement This work is currently carried out within the scope of the AIM@SHAPE Network of Excellence-Advanced and Innovative Models and Tools for the development of Semanticbased systems for Handling  ...  class), • m+ for a positive minimum (PositiveCurvatureMinimum class), • M− for a negative maximum (NegativeCurvatureMaximum class), • m− for a negative minimum (NegativeCurvatureMinimum class), and •  ... 
doi:10.1080/09544820701403714 fatcat:2sgfxszts5cvzjm2wkcnvpeum4

Not Using the Car to See the Sidewalk — Quantifying and Controlling the Effects of Context in Classification and Segmentation

Rakshith Shetty, Bernt Schiele, Mario Fritz
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
We apply this methodology on two tasks, image classification and semantic segmentation, and discover undesirable dependency between objects and context, for example that "sidewalk" segmentation is very  ...  sensitive to the presence of "cars" in the image.  ...  Semantic segmentation.  ... 
doi:10.1109/cvpr.2019.00841 dblp:conf/cvpr/ShettySF19 fatcat:xqwtlhuqqff3nk2xjzukfk6dmq

Self-Driving Cars: A Survey [article]

Claudine Badue, Rânik Guidolini, Raphael Vivacqua Carneiro, Pedro Azevedo, Vinicius Brito Cardoso, Avelino Forechi, Luan Jesus, Rodrigo Berriel, Thiago Paixão, Filipe Mutz, Lucas Veronese, Thiago Oliveira-Santos (+1 others)
2019 arXiv   pre-print
In this survey, we present the typical architecture of the autonomy system of self-driving cars. We also review research on relevant methods for perception and decision making.  ...  The perception system is generally divided into many subsystems responsible for tasks such as self-driving-car localization, static obstacles mapping, moving obstacles detection and tracking, road mapping  ...  Xu et al. (2015) describe the context-aware tracking of moving obstacles for distance keeping used by the new experimental self-driving car of the Carnegie Mellon University.  ... 
arXiv:1901.04407v2 fatcat:uwrgi5wjlbckdhtyy4eelinmde

Advanced eNose-Driven Pedestrian Tracking Pipeline for Intelligent Car Driver Assisting System: Preliminary Results

Francesco Rundo, Ilaria Anfuso, Maria Grazia Amore, Alessandro Ortis, Angelo Messina, Sabrina Conoci, Sebastiano Battiato
2022 Sensors  
The authors propose a full, deep pipeline for the identification, monitoring and tracking of the salient pedestrians, combined with an intelligent electronic alcohol sensing system to properly assess the  ...  Car drivers must keep a safe driving dynamic, having an unaltered physiological status while processing the surrounding information coming from the driving scenario (e.g., traffic signs, other vehicles  ...  These feature representations achieve mutual gains and are more robust for semantic segmentation.  ... 
doi:10.3390/s22020674 pmid:35062635 pmcid:PMC8780914 fatcat:3ezsy62atber5j7tw6rdj3jcgu

LLDNet: A Lightweight Lane Detection Approach for Autonomous Cars Using Deep Learning

Md. Al-Masrur Khan, Md Foysal Haque, Kazi Rakib Hasan, Samah H. Alajmani, Mohammed Baz, Mehedi Masud, Abdullah-Al Nahid
2022 Sensors  
Lane detection plays a vital role in making the idea of the autonomous car a reality.  ...  In recent years, Deep Learning (DL) models, especially Convolutional Neural Network (CNN) models have been proposed and utilized to perform pixel-level lane segmentation.  ...  We also cordially thank the Youtube channel dxer manto for permitting us to use their Youtube videos in our research. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22155595 pmid:35898103 pmcid:PMC9332112 fatcat:2ry2uixhdbdkxjcsez46sezequ

CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020

2020 International Journal of Computer Assisted Radiology and Surgery  
The traditional platforms of CARS Congresses for the scholarly publication and communication process for the presentation of R&D ideas were congress centers or hotels, typically hosting 600-800 participants  ...  Aiming to stimulate complimentary thoughts and actions on what is being presented at CARS, implies a number of enabling variables for optimal analogue scholarly communication, such as (examples given are  ...  Therefore, a master-slave robotic system for VI is necessary for minimization of the radiation exposure.  ... 
doi:10.1007/s11548-020-02171-6 pmid:32514840 fatcat:lyhdb2zfpjcqbf4mmbunddwroq

CARS 2021: Computer Assisted Radiology and Surgery Proceedings of the 35th International Congress and Exhibition Munich, Germany, June 21–25, 2021

2021 International Journal of Computer Assisted Radiology and Surgery  
Semantic segmentation (SS) is one of the labeling methods that associate each pixel of an image with a class label.  ...  ; and none for the HC class.  ... 
doi:10.1007/s11548-021-02375-4 pmid:34085172 fatcat:6d564hsv2fbybkhw4wvc7uuxcy

CARS 2016—Computer Assisted Radiology and Surgery Proceedings of the 30th International Congress and Exhibition Heidelberg, Germany, June 21–25, 2016

2016 International Journal of Computer Assisted Radiology and Surgery  
We would like to thank the Spanish company BQ for the donation of the 3D printing hardware for clinical use.  ...  '', and Amazon Inc., for providing valuable computing resources through an ''AWS in Education Research'' grant.  ...  papers are reviewed for regular issues of IJCARS, and if applicable (i.e. if requested by the authors), also for presentation at the CARS congress.  ... 
doi:10.1007/s11548-016-1412-5 pmid:27206418 fatcat:uk5r46n2xvhedkfjzmeiweyneq

The Analysis of the Epic Poem of the Kosovo Cycle Car Lazar i carica Milica and Its Translation into English [chapter]

Dragana Janković
2020 Belgrade English Language and Literature Studies  
This paper will be based on an analysis of the Serbian epic poem of the Kosovo cycle Car Lazar i carica Milica and its translations into English.  ...  However, it is expected that, when translating such texts, translators be aware of the qualities of the original as the bearer of the culture and tradition of a people.  ...  ) I go, to shed my blood for Jesus' sake Noyes and Bacon: 10) a) to perish for Christ his Cross and Faith on the field of Kosovo b) I would ride to death for the Cross and the Faith on level Kosovo Nor  ... 
doi:10.18485/bells90.2020.1.ch33 fatcat:liozwtqwgjdt5gjlnky2qrwne4

Learning Semantic-Aware Dynamics for Video Prediction [article]

Xinzhu Bei, Yanchao Yang, Stefano Soatto
2021 arXiv   pre-print
The result is a predictive model that explicitly represents objects and learns their class-specific motion, which we evaluate on video prediction benchmarks.  ...  The appearance of the scene is warped from past frames using the predicted motion in co-visible regions; dis-occluded regions are synthesized with content-aware inpainting utilizing the predicted scene  ...  For example, we input the "car" segments to the semantic-aware encoder that learns the dynamics of the "road" class, and vice versa.  ... 
arXiv:2104.09762v1 fatcat:rzbewbus4zftpn6cu4e6asfoi4
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