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Learning Direct Optimization for Scene Understanding [article]

Lukasz Romaszko, Christopher K.I. Williams, John Winn
2018 arXiv   pre-print
We introduce a Learning Direct Optimization method for the refinement of a latent variable model that describes input image x.  ...  Our novel Learning Direct Optimization (LiDO) approach trains a Prediction Network to predict an update directly to correct z, rather than minimizing the error with respect to z.  ...  Supplementary Material for: Learning Direct Optimization for Scene Understanding Detector and Initialization Networks . . . . . 13 D.2. LiDO Prediction Network . . . . . . . . . . 13 A.  ... 
arXiv:1812.07524v1 fatcat:bgnahxc24jdwpavvjdmitiiiei

DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization [article]

Cheng Zhang, Zhaopeng Cui, Cai Chen, Shuaicheng Liu, Bing Zeng, Hujun Bao, Yinda Zhang
2021 arXiv   pre-print
image quality for total panoramic 3D scene understanding.  ...  In this paper, we propose a novel method for panoramic 3D scene understanding which recovers the 3D room layout and the shape, pose, position, and semantic category for each object from a single full-view  ...  To learn and evaluate our model, a new dataset is created for total panoramic 3D scene understanding.  ... 
arXiv:2108.10743v1 fatcat:knc6p65etvfihcb6rey3oihrfu

Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models [article]

Congcong Li, Adarsh Kowdle, Ashutosh Saxena, Tsuhan Chen
2011 arXiv   pre-print
Scene understanding includes many related sub-tasks, such as scene categorization, depth estimation, object detection, etc.  ...  We propose Feedback Enabled Cascaded Classification Models (FE-CCM), that jointly optimizes all the sub-tasks, while requiring only a 'black-box' interface to the original classifier for each sub-task.  ...  ACKNOWLEDGMENTS We thank Anish Nahar, Matthew Cong, TP Wong, Norris Xu, and Colin Ponce for help with the robotic experiments. We also thank Daphne Koller for useful discussions.  ... 
arXiv:1110.5102v1 fatcat:abtffcuzkvftbhk5s3yi2og7y4

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  ...  The intuition behind is to leverage the coupled nature of these two tasks to improve the granularity and performance of scene understanding.  ...  . • E hoi models HOI and provides strong and fine-grained constraints for holistic scene understanding.  ... 
arXiv:1909.01507v1 fatcat:svbd33j7hvaz5jbysjwwhqhnoy

Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification [article]

Jie Chen, Haozhe Huang, Jian Peng, Jiawei Zhu, Li Chen, Wenbo Li, Binyu Sun, Haifeng Li
2020 arXiv   pre-print
In this paper, we proposed an automatically architecture learning procedure for remote sensing scene classification.  ...  To discover the optimal set of parameters for a given dataset, we introduced a learning strategy which can allow efficient search in the architecture space by means of gradient descent.  ...  Architecture determines the function of CNN, this architecture-learned method may help to understand which representations are important for remote sensing scene classification tasks. II.  ... 
arXiv:2001.09614v1 fatcat:drfzcrelbrhgngujdgrk3uu2ee

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  ...  The intuition behind is to leverage the coupled nature of these two tasks to improve the granularity and performance of scene understanding.  ...  All the evidence calls for a treatment to integrate HOI and physical commonsense with a modern computer vision system for scene understanding.  ... 
doi:10.1109/iccv.2019.00874 dblp:conf/iccv/ChenHYZQZ19 fatcat:2dutdksvzjgind7okkv7puymmm

Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis [article]

Julian Knodt, Joe Bartusek, Seung-Hwan Baek, Felix Heide
2021 arXiv   pre-print
We validate the proposed approach for scene editing, relighting and reflectance estimation learned from synthetic and captured views on a subset of NeRV's datasets.  ...  The method outperforms NeRV for relighting under known lighting conditions, and produces realistic reconstructions for relit and edited scenes.  ...  We also demonstrate the understandibility of our model, by showing surface normals and incoming light directions along the surface, by modifying integrators.  ... 
arXiv:2104.13562v2 fatcat:bgy25vm77jaudfcx4l4ftvwvfq

Insights into few shot learning approaches for image scene classification

Mohamed Soudy, Yasmine Afify, Nagwa Badr
2021 PeerJ Computer Science  
Notwithstanding the optimal performance of exiting machine learning models in image understanding and scene classification, there are still obstacles to overcome.  ...  Motivated by these findings, in this paper, we introduce two models for few-shot learning in scene classification.  ...  Despite the optimal performance of existing models in image understanding and scene classification, there are still major issues.  ... 
doi:10.7717/peerj-cs.666 pmid:34616882 pmcid:PMC8459776 fatcat:uzwb5qlf75ba3as6jwu4oaoukq

An Overview of Perception and Decision-Making in Autonomous Systems in the Era of Learning [article]

Yang Tang, Chaoqiang Zhao, Jianrui Wang, Chongzhen Zhang, Qiyu Sun, Weixing Zheng, Wenli Du, Feng Qian, Juergen Kurths
2020 arXiv   pre-print
Finally, we examine the several challenges and promising directions discussed and concluded in related research for future works in the era of computer science, automatic control, and robotics.  ...  First, we delineate the existing classical simultaneous localization and mapping (SLAM) solutions and review the environmental perception and understanding methods based on deep learning, including deep  ...  It is a development direction for autonomous systems to realize the optimal strategy for task assignment ac-cording to the current state of robots and task requirements.  ... 
arXiv:2001.02319v3 fatcat:z3zhp2cyonfqtlttl2y57572uy

Deep Learning Driven Visual Path Prediction From a Single Image

Siyu Huang, Xi Li, Zhongfei Zhang, Zhouzhou He, Fei Wu, Wei Liu, Jinhui Tang, Yueting Zhuang
2016 IEEE Transactions on Image Processing  
Its goal is to infer the future path for a visual object in a static scene.  ...  Motivated by these observations, we propose a deep learning framework which simultaneously performs deep feature learning for visual representation in conjunction with spatio-temporal context modeling.  ...  Which one is optimal? P 3 wins out because its initial direction θ P3 is closer to θ esti .  ... 
doi:10.1109/tip.2016.2613686 pmid:28114063 fatcat:vnvwbkv2vvhodbvha3jjuuzwqu

Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation [article]

Abhijit Kundu, Kyle Genova, Xiaoqi Yin, Alireza Fathi, Caroline Pantofaru, Leonidas Guibas, Andrea Tagliasacchi, Frank Dellaert, Thomas Funkhouser
2022 arXiv   pre-print
During experiments with real-world dynamic scenes, we find that our model can be used effectively for several tasks like novel view synthesis, 2D panoptic segmentation, 3D scene editing, and multiview  ...  Each object is represented by an oriented 3D bounding box and a multi-layer perceptron (MLP) that takes position, direction, and time and outputs density and radiance.  ...  We use Adam as our optimizer for all our training routines including optimizing Panoptic Neural Field model to a new scene and also during inner loops of FedAvg based meta-learning (see Sec. 3.4) for learned  ... 
arXiv:2205.04334v1 fatcat:ukrp6g5wurbblmj6pbjlclu2im

Convex Optimization for Scene Understanding

Mohamed Souiai, Claudia Nieuwenhuis, Evgeny Strekalovskiy, Daniel Cremers
2013 2013 IEEE International Conference on Computer Vision Workshops  
In this paper we give a convex optimization approach for scene understanding.  ...  Since segmentation, object recognition and scene labeling strongly benefit from each other we propose to solve these tasks within a single convex optimization problem.  ...  Solving these tasks within a single optimization problem such that all tasks can influence each other improves results for scene understanding.  ... 
doi:10.1109/iccvw.2013.131 dblp:conf/iccvw/SouiaiNSC13 fatcat:4svrxguclbca5ezvsfn6z2upmy

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose [article]

Zhichao Yin, Jianping Shi
2018 arXiv   pre-print
We propose GeoNet, a jointly unsupervised learning framework for monocular depth, optical flow and ego-motion estimation from videos.  ...  The three components are coupled by the nature of 3D scene geometry, jointly learned by our framework in an end-to-end manner.  ...  Acknowledgements We would like to thank Guorun Yang and Tinghui Zhou for helpful discussions and sharing the code. We also thank the anonymous reviewers for their instructive comments.  ... 
arXiv:1803.02276v2 fatcat:rcqfxt53qzfehb2uiqoav7w42e

GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose

Zhichao Yin, Jianping Shi
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
We propose GeoNet, a jointly unsupervised learning framework for monocular depth, optical flow and egomotion estimation from videos.  ...  The three components are coupled by the nature of 3D scene geometry, jointly learned by our framework in an end-to-end manner.  ...  Supervised Deep Models for Geometry Understanding With recent development of deep learning, great progress has been made in many tasks of 3D geometry understanding, including depth, optical flow, pose  ... 
doi:10.1109/cvpr.2018.00212 dblp:conf/cvpr/YinS18 fatcat:osotve7hgvetdgp6d5hvv2u32q

Developing an Interactive 3D Learning Experience to Help Students Understand Key Regulatory Processes Associated with Glycolysis

Jacqueline Mason, Kevin Brennan, Samantha Bond, Leah Lebowicz
2018 Journal of Biocommunication  
Recent recommendations for undergraduate biologyinstruction emphasize teaching foundational biologicalprinciples and helping students transfer these principles tomore complex biological phenomena.  ...  The following researchproject was developed to explore whether a visualinteractive didactic tool could be developed to improvelearning outcomes for undergraduate biology students onthe topic of allosteric  ...  The finished application and 2D animation were optimized and exported for web delivery (see figures 6 and 7). The landing page contains a brief introduction along with the 2D animation.  ... 
doi:10.5210/jbc.v42i1.9193 fatcat:pyddxqm5xfamdazxw3pqhlnwqe
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