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Data-driven contextual modeling for 3D scene understanding

Yifei Shi, Pinxin Long, Kai Xu, Hui Huang, Yueshan Xiong
2016 Computers & graphics  
A set of classifiers are trained for both individual objects and object groups, using a database of 3D scene models.  ...  To address the specific challenges in object analysis at subscene level, this work proposes a data-driven approach to modeling contextual information covering both intra-object part relations and inter-object  ...  Acknowledgements 644 We thank all the reviewers for their comments and feed-645 back. We would also like to acknowledge our research  ... 
doi:10.1016/j.cag.2015.11.003 fatcat:son2advklbfyjibhb3i4kghh5u

Analysis and Modeling of 3D Indoor Scenes [article]

Rui Ma
2017 arXiv   pre-print
We first review works on understanding and semantic modeling of scenes from captured 3D data of the real world.  ...  Then, we focus on the virtual scenes composed of 3D CAD models and study methods for 3D scene analysis and processing.  ...  Object recognition from captured 3D data is the main task for 3D scene understanding.  ... 
arXiv:1706.09577v1 fatcat:pdbztyjkezabnj3eaok5wrs7xq

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection

Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Yiming Zhang, Kai Xu, Jun Wang
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Finally, a Global Scene Context (GSC) module is designed to learn the global scene context. We demonstrate these by capturing contextual information at patch, object and scene levels.  ...  Specifically, a Patch-to-Patch Context (PPC) module is employed to capture contextual information between the point patches, before voting for their corresponding object centroid points.  ...  Acknowledgment This work was supported in part by National Natural Science Foundation of China under Grant (61772267, 61572507, 61532003, 61622212), the Fundamental Research Funds for the Central Universities  ... 
doi:10.1109/cvpr42600.2020.01046 dblp:conf/cvpr/XieLWWZXW20 fatcat:4pbayaozwnbhrji5gikw3zehsm

Alvey MMI-007 Vehicle Exemplar: The Knowledge Based Approach

K. D. Baker, G. D. Sullivan
1987 Procedings of the Alvey Vision Conference 1987  
Perceptual organisation has played an important role in the model driven approach to image understanding developed by Lowe.  ...  Establishing the correspondence between 2D image features and 3D object components is the major problem in model driven vision systems.  ... 
doi:10.5244/c.1.1 dblp:conf/bmvc/BakerS87 fatcat:hhuewgileretroneijspzz65em

Data-Driven Shape Analysis and Processing

Kai Xu, Vladimir G. Kim, Qixing Huang, Evangelos Kalogerakis
2016 Computer graphics forum (Print)  
In contrast to traditional approaches that process shapes in isolation of each other, data-driven methods aggregate information from 3D model collections to improve the analysis, modelling and editing  ...  Data-driven methods are also able to learn computational models that reason about properties and relationships of shapes without relying on hardcoded rules or explicitly programmed instructions.  ...  Acknowledgements We thank Zimo Li for proofreading this survey and the anonymous reviewers for helpful suggestions. Kalogerakis gratefully acknowledges support from NSF (CHS-1422441).  ... 
doi:10.1111/cgf.12790 fatcat:q76sq2syjvce5fjjjb7yoafww4

Automatic semantic modeling of indoor scenes from low-quality RGB-D data using contextual information

Kang Chen, Yu-Kun Lai, Yu-Xin Wu, Ralph Martin, Shi-Min Hu
2014 ACM Transactions on Graphics  
Figure 1 : Automatic semantic modeling of an office scene. Left: input RGB-D images, right: reconstructed 3D scene.  ...  In seconds, we output a visually plausible 3D scene, adapting these models and their parts to fit the input scans.  ...  Many 3D models are accessible online, which permits the development of data-driven methods to semantically reconstruct scenes.  ... 
doi:10.1145/2661229.2661239 fatcat:mrrmxatpffeataaosijgji6eqi

Data-Driven Shape Analysis and Processing [article]

Kai Xu, Vladimir G. Kim, Qixing Huang, Evangelos Kalogerakis
2015 arXiv   pre-print
Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent  ...  modeling, editing, and visualization of geometric data.  ...  In a sense, data-driven methods close the loop of data generation and data analysis for 3D shapes and scenes; see Figure 2 .  ... 
arXiv:1502.06686v1 fatcat:upajios4y5a6dgf2zw7faqai4a

MLCVNet: Multi-Level Context VoteNet for 3D Object Detection [article]

Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Yiming Zhang, Kai Xu, Jun Wang
2020 arXiv   pre-print
Finally, a Global Scene Context (GSC) module is designed to learn the global scene context. We demonstrate these by capturing contextual information at patch, object and scene levels.  ...  Specifically, a Patch-to-Patch Context (PPC) module is employed to capture contextual information between the point patches, before voting for their corresponding object centroid points.  ...  [36, 37] , and 3D scene understanding [12, 13] .  ... 
arXiv:2004.05679v1 fatcat:ndwen6745ve7dljivybm2qav7i

Data-driven shape analysis and processing

Kai Xu, Vladimir G. Kim, Qixing Huang, Niloy Mitra, Evangelos Kalogerakis
2016 SIGGRAPH ASIA 2016 Courses on - SA '16  
, etc.), offer great opportunities for developing data-driven approaches for 3D shape analysis and processing.  ...  Prior to the emergence of data-driven techniques, high-level shape understanding and modeling was usually achieved with knowledge-driven methods.  ...  Acknowledgements We thank Zimo Li for proofreading this survey and the anonymous reviewers for helpful suggestions. Kalogerakis gratefully acknowledges support from NSF (CHS-1422441).  ... 
doi:10.1145/2988458.2988473 dblp:conf/siggraph/0004KHMK16 fatcat:tefja76ijnclzmpux2iaj45zgu

Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense [article]

Yixin Chen, Siyuan Huang, Tao Yuan, Siyuan Qi, Yixin Zhu, Song-Chun Zhu
2019 arXiv   pre-print
We propose a new 3D holistic++ scene understanding problem, which jointly tackles two tasks from a single-view image: (i) holistic scene parsing and reconstruction---3D estimations of object bounding boxes  ...  (ii) physical commonsense to model the physical plausibility of the reconstructed scene.  ...  . • E hoi models HOI and provides strong and fine-grained constraints for holistic scene understanding.  ... 
arXiv:1909.01507v1 fatcat:svbd33j7hvaz5jbysjwwhqhnoy

Lifting GIS Maps into Strong Geometric Context for Scene Understanding [article]

Raúl Díaz, Minhaeng Lee, Jochen Schubert, Charless C. Fowlkes
2016 arXiv   pre-print
We present a pipeline to quickly generate strong 3D geometric priors from 2D GIS data using SfM models aligned with minimal user input.  ...  We propose to leverage such information for scene understanding by combining GIS resources with large sets of unorganized photographs using Structure from Motion (SfM) techniques.  ...  GIS for image understanding The role of GIS map data in automatically interpreting images of outdoor scenes appears to have received relatively little attention in computer vision.  ... 
arXiv:1507.03698v4 fatcat:cgt7mrjhq5airoutekbhhqchx4

Holistic++ Scene Understanding: Single-View 3D Holistic Scene Parsing and Human Pose Estimation With Human-Object Interaction and Physical Commonsense

Yixin Chen, Siyuan Huang, Tao Yuan, Yixin Zhu, Siyuan Qi, Song-Chun Zhu
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
We propose a new 3D holistic ++ scene understanding problem, which jointly tackles two tasks from a single-view image: (i) holistic scene parsing and reconstruction-3D estimations of object bounding boxes  ...  (ii) physical commonsense to model the physical plausibility of the reconstructed scene.  ...  . • E hoi models HOI and provides strong and fine-grained constraints for holistic scene understanding.  ... 
doi:10.1109/iccv.2019.00874 dblp:conf/iccv/ChenHYZQZ19 fatcat:2dutdksvzjgind7okkv7puymmm

PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding [chapter]

Yinda Zhang, Shuran Song, Ping Tan, Jianxiong Xiao
2014 Lecture Notes in Computer Science  
To overcome this limitation, we advocate the use of 360 • full-view panoramas in scene understanding, and propose a whole-room context model in 3D.  ...  To train our model, we construct an annotated panorama dataset and reconstruct the 3D model from single-view using manual annotation.  ...  We propose a non-parametric data-driven brute-force context model by aligning a hypothesis with the 3D rooms from the training set.  ... 
doi:10.1007/978-3-319-10599-4_43 fatcat:rikrktadsjclhes6gjqrjgbqge

Context Aware Video Caption Generation with Consecutive Differentiable Neural Computer

Jonghong Kim, Inchul Choi, Minho Lee
2020 Electronics  
DNC naturally learns to use its internal memory for context understanding and also provides contents of its memory as an output for additional connection.  ...  In experiments, we demonstrate that our model provides more natural and coherent captions which reflect previous contextual information.  ...  From the current scene, 3D CNN extracts valuable information as feature map.  ... 
doi:10.3390/electronics9071162 fatcat:3rxsucooxrcwplqgfgr6dz7xdi

A Relevancy, Hierarchical and Contextual Maximum Entropy Framework for a Data-Driven 3D Scene Generation

Mesfin Dema, Hamed Sari-Sarraf
2014 Entropy  
We introduce a novel Maximum Entropy (MaxEnt) framework that can generate 3D scenes by incorporating objects' relevancy, hierarchical and contextual constraints in a unified model.  ...  This model is formulated by a Gibbs distribution, under the MaxEnt framework, that can be sampled to generate plausible scenes.  ...  proposed an automatic data-driven 3D object modeling system based on Bayesian network formulation.  ... 
doi:10.3390/e16052568 fatcat:wrtvbqusu5ajnkrhyx2tf7qqli
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