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Object location in realistic networks

Kirsten Hildrum, Robert Krauthgamer, John Kubiatowicz
2004 Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures - SPAA '04  
We devise an object location scheme that achieves a guaranteed low stretch in a wider and more realistic class of networks than previous schemes.  ...  As a byproduct, our scheme has several advantages over existing ones, such as robustness to errors in network measurements, and simpler design choices of system builders, which may lead to improved and  ...  Our Results We present a scheme that achieves a guaranteed low stretch object location without requiring a global growth rate bound C, and is thus effective in a wider and more realistic class of networks  ... 
doi:10.1145/1007912.1007918 dblp:conf/spaa/HildrumKK04 fatcat:tltwwvjv7rbz5pe4ef72znm3ry

Deep Structured Generative Models [article]

Kun Xu, Haoyu Liang, Jun Zhu, Hang Su, Bo Zhang
2018 arXiv   pre-print
In particular, the layout or structure of the scene is encoded by a stochastic and-or graph (sAOG), in which the terminal nodes represent single objects and edges represent relations between objects.  ...  Deep generative models have shown promising results in generating realistic images, but it is still non-trivial to generate images with complicated structures.  ...  Experimental results demonstrate that sAOG can model the intrinsic structure of complicated relations between objects in an image, and can direct the refinement network to produce realistic images in a  ... 
arXiv:1807.03877v1 fatcat:uqwtxywiu5b2tiyckppnyhyaku

Fast synthetic dataset for kitchen object segmentation in deep learning

Ruben Sagues-Tanco, Luis Benages-Pardo, Gonzalo Lopez-Nicolas, Sergio Llorente
2020 IEEE Access  
Currently, this process is carried out through neural networks, but there are very few public datasets available with mask and class labels of the objects for the training process in usual applications  ...  In the experimental evaluation, we study both synthetic datasets, automatic or realistic, and we compare the results.  ...  The goal is to locate the presence of objects in a specific environment with their corresponding bounding box and mask, as well as the ability to detect the classes of the located objects in the image.  ... 
doi:10.1109/access.2020.3043256 fatcat:qq64azxvbngddodlzzb275xa2i

Inserting Videos Into Videos

Donghoon Lee, Tomas Pfister, Ming-Hsuan Yang
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Our main task is, given an object video and a scene video, to insert the object video at a user-specified location in the scene video so that the resulting video looks realistic.  ...  To synthesize a realistic video, the network renders each frame based on the current input and previous frames.  ...  Introduction Object insertion in images aims to insert a new object into a given scene such that the manipulated scene looks realistic.  ... 
doi:10.1109/cvpr.2019.01030 dblp:conf/cvpr/LeeP019 fatcat:fytytpthdvcwng7tbgcli5hwyq

Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks [article]

Ali Diba, Vivek Sharma, Rainer Stiefelhagen, Luc Van Gool
2018 arXiv   pre-print
We demonstrate that the network can act as an encoder-decoder generating parts of an image which contain an object, or as a modified deep CNN to rep- resent images for object detection in supervised and  ...  localizing different categories in images for weakly supervised object detection; and 3) improving object discov- ery in object detection pipelines.  ...  The image is encoded by a CNN and our generative network draws a realistic sample of a specific object in the image using indication of its location.  ... 
arXiv:1711.08174v2 fatcat:tzoog5czkvgnjekwtkziu55p2a

Weakly Supervised Object Discovery by Generative Adversarial & Ranking Networks

Ali Diba, Vivek Sharma, Rainer Stiefelhagen, Luc Van Gool
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We demonstrate that the network can act as an encoder-decoder generating parts of an image which contain an object, or as a modified deep CNN to represent images for object detection in supervised and  ...  localizing different categories in images for weakly supervised object detection; and 3) improving object discovery in object detection pipelines.  ...  The image is encoded by a CNN and our generative network draws a realistic sample of a specific object in the image using indication of its location.  ... 
doi:10.1109/cvprw.2019.00086 dblp:conf/cvpr/DibaSSG19 fatcat:3h4q3uv66rcurjadajejwzslfi

A new 'Direction' for source location privacy in wireless sensor networks'

Shehla S Rana, Nitin H. Vaidya
2012 2012 IEEE Global Communications Conference (GLOBECOM)  
Preserving source location privacy in wireless sensor networks can be critical for several practical applications.  ...  We show how use of directional antennas makes eavesdropping more costly for a realistic adversary and establish relationships between probability of compromise of location privacy, characteristics of directional  ...  ACKNOWLEDGMENT This research is supported in part by Army Research Office grant W-911-NF-0710287.  ... 
doi:10.1109/glocom.2012.6503136 dblp:conf/globecom/RanaV12 fatcat:epg3yqunpfhxtkymap25mzcpxm

Unsupervised Holistic Image Generation from Key Local Patches [chapter]

Donghoon Lee, Sangdoo Yun, Sungjoon Choi, Hwiyeon Yoo, Ming-Hsuan Yang, Songhwai Oh
2018 Lecture Notes in Computer Science  
In this work, key local patches are defined as informative regions of the target object or scene.  ...  This is a challenging problem since it requires generating realistic images and predicting locations of parts at the same time. We construct adversarial networks to tackle this problem.  ...  generates realistic images and predict part locations well.  ... 
doi:10.1007/978-3-030-01228-1_2 fatcat:ij3g5gacynaprisescxorxe7dm

Introduction to the Special Issue on Location Modeling

Michael J. Kuby, Richard Church
2010 Networks and Spatial Economics  
Researchers have explored different solution spaces (planar, network, discrete, spherical, and hybrid), numerous objectives (single vs. multiple), temporal aspects (static vs. dynamic), the nature of demand  ...  The papers in this special issue of Networks and Spatial Economics are expanded and refined treatments of topics identified at ISOLDE XI, held in Santa Barbara CA in 2008, as central to current scholarly  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided  ... 
doi:10.1007/s11067-010-9136-5 fatcat:okmkc7jxqfdibkwv3qjtwbcyhi

Repopulating Street Scenes [article]

Yifan Wang, Andrew Liu, Richard Tucker, Jiajun Wu, Brian L. Curless, Steven M. Seitz, Noah Snavely
2021 arXiv   pre-print
in scenes that respects scene geometry and illumination.  ...  At a technical level, our work has three primary contributions: (1) a method for clearing images of objects, (2) a method for estimating sun direction from a single image, and (3) a way to compose objects  ...  Both networks realistically inpaint the object region; however, CRA fails to remove object shadows since they are not included in the mask.  ... 
arXiv:2103.16183v1 fatcat:ry6fcodhfnghhna7jhdirjprp4

Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination [article]

Pratul P. Srinivasan, Ben Mildenhall, Matthew Tancik, Jonathan T. Barron, Richard Tucker, Noah Snavely
2020 arXiv   pre-print
We demonstrate that our method can predict consistent spatially-varying lighting that is convincing enough to plausibly relight and insert highly specular virtual objects into real images.  ...  We present a deep learning solution for estimating the incident illumination at any 3D location within a scene from an input narrow-baseline stereo image pair.  ...  we use for supervision are representative of realistic object insertion locations.  ... 
arXiv:2003.08367v2 fatcat:jvho3ft4evbelar2efnfyjvwhe

Unsupervised Holistic Image Generation from Key Local Patches [article]

Donghoon Lee, Sangdoo Yun, Sungjoon Choi, Hwiyeon Yoo, Ming-Hsuan Yang, Songhwai Oh
2017 arXiv   pre-print
In this work, key local patches are defined as informative regions of the target object or scene.  ...  This is a challenging problem since it requires generating realistic images and predicting locations of parts at the same time. We construct adversarial networks to tackle this problem.  ...  can generate realistic images and predict part locations well.  ... 
arXiv:1703.10730v2 fatcat:f4nxmfk7d5fzjmkrt6ffwyymay

Toward Volume-Based Haptic Collaborative Virtual Environment with Realistic Sensation

Takahide Tanaka, Satoshi Yamaguchi, Lee Jooho, Nobutaka Shimada, Hiromi T. Tanaka
2008 2008 Second International Symposium on Universal Communication  
In this paper, we propose a volume-based realistic communication system called Haptic Communication that allows participants to interact in real-time with others at remote locations on the network in haptic  ...  At first virtual soft objects are represented by adaptive volume model in the PCs at the remote locations.  ...  In this study, we constructed our system as follows. First, an adaptive volume model represents virtual soft objects in the PCs at remote locations.  ... 
doi:10.1109/isuc.2008.47 dblp:conf/iucs/TanakaYJST08 fatcat:vtefkzeuufcjnp5qo2yxe4gu4y

Event-driven, role-based mobility in disaster recovery networks

Samuel C. Nelson, Albert F. Harris, Robin Kravets
2007 Proceedings of the second workshop on Challenged networks CHANTS - CHANTS '07  
While many mobility models exist for simulating ad hoc networks, they do not realistically capture the behavior of objects in disaster scenarios.  ...  Furthermore, to incorporate reaction from multiple events in a realistic fashion, we propose a low-level gravity-based mobility model in which events apply forces to objects.  ...  Many roles in disaster networks must react to multiple events by fleeing or approaching in a realistic fashion.  ... 
doi:10.1145/1287791.1287798 dblp:conf/mobicom/NelsonHK07 fatcat:j7xj3p45s5ex5h5dlilng7i72i

Enhanced novelty detection in auditory scenes through adaptation of inhibition

Bertrand Fontaine
2015 BMC Neuroscience  
In this work I am interested in the neural mechanisms underlying detection of novel objects in auditory scenes, such as a novel sound source at a given location.  ...  In this study I seek to test functions of enhancement effects in realistic listening situations.  ...  In this work I am interested in the neural mechanisms underlying detection of novel objects in auditory scenes, such as a novel sound source at a given location.  ... 
doi:10.1186/1471-2202-16-s1-p72 pmcid:PMC4697530 fatcat:7fq4tlfifnglhmjwntqia345yi
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