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Ali Farhadi | Abhinav Gupta | Roozbeh Mottaghi | Mohammad Rastegari | A. Gupta | Ali Farhadi | R. Mottaghi | Mohammad Rastegari | Roozbeh Mottaghi
[1] Steven M. Seitz,et al. Computing the Physical Parameters of Rigid-Body Motion from Video , 2002, ECCV.
[2] Antonio Torralba,et al. Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes , 2003, NIPS.
[3] Geoffrey E. Hinton,et al. The Recurrent Temporal Restricted Boltzmann Machine , 2008, NIPS.
[4] Odest Chadwicke Jenkins,et al. Physical simulation for probabilistic motion tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[5] Ashutosh Saxena,et al. Cascaded Classification Models: Combining Models for Holistic Scene Understanding , 2008, NIPS.
[6] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[7] David J. Fleet,et al. Estimating contact dynamics , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[8] Li Fei-Fei,et al. Towards total scene understanding: Classification, annotation and segmentation in an automatic framework , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[9] Alexei A. Efros,et al. Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics , 2010, ECCV.
[10] Antonio Torralba,et al. A Data-Driven Approach for Event Prediction , 2010, ECCV.
[11] Jessica B. Hamrick,et al. Probabilistic internal physics models guide judgments about object dynamics , 2011, CogSci.
[12] Jessica B. Hamrick. Internal physics models guide probabilistic judgments about object dynamics , 2011 .
[13] Raquel Urtasun,et al. Physically-based motion models for 3D tracking: A convex formulation , 2011, 2011 International Conference on Computer Vision.
[14] Martial Hebert,et al. Activity Forecasting , 2012, ECCV.
[15] Yun Jiang,et al. Learning to place new objects in a scene , 2012, Int. J. Robotics Res..
[16] Sanja Fidler,et al. Describing the scene as a whole: Joint object detection, scene classification and semantic segmentation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[17] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[18] Derek Hoiem,et al. Indoor Segmentation and Support Inference from RGBD Images , 2012, ECCV.
[19] Jessica B. Hamrick,et al. Simulation as an engine of physical scene understanding , 2013, Proceedings of the National Academy of Sciences.
[20] Tsuhan Chen,et al. 3D-Based Reasoning with Blocks, Support, and Stability , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Sanja Fidler,et al. Holistic Scene Understanding for 3D Object Detection with RGBD Cameras , 2013, 2013 IEEE International Conference on Computer Vision.
[22] Silvio Savarese,et al. Understanding Indoor Scenes Using 3D Geometric Phrases , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Katsushi Ikeuchi,et al. Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.
[25] Katsushi Ikeuchi,et al. Detecting potential falling objects by inferring human action and natural disturbance , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[26] Arnold W. M. Smeulders,et al. Déjà Vu: - Motion Prediction in Static Images , 2018, ECCV.
[27] Marc'Aurelio Ranzato,et al. Video (language) modeling: a baseline for generative models of natural videos , 2014, ArXiv.
[28] Roland Memisevic,et al. Modeling Deep Temporal Dependencies with Recurrent "Grammar Cells" , 2014, NIPS.
[29] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[30] Yinda Zhang,et al. PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding , 2014, ECCV.
[31] David F. Fouhey,et al. Predicting Object Dynamics in Scenes , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[32] Martial Hebert,et al. Patch to the Future: Unsupervised Visual Prediction , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[33] Martial Hebert,et al. Dense Optical Flow Prediction from a Static Image , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[34] Abhinav Gupta,et al. Designing deep networks for surface normal estimation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Jiajun Wu,et al. Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning , 2015, NIPS.
[36] Jianxiong Xiao,et al. SUN RGB-D: A RGB-D scene understanding benchmark suite , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[37] Roberto Cipolla,et al. SceneNet: Understanding Real World Indoor Scenes With Synthetic Data , 2015, ArXiv.
[38] Geoffrey E. Hinton,et al. A Simple Way to Initialize Recurrent Networks of Rectified Linear Units , 2015, ArXiv.
[39] Pushmeet Kohli,et al. Computationally bounded retrieval , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Samy Bengio,et al. Show and tell: A neural image caption generator , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[41] S. Levine,et al. Predictive Visual Models of Physics for Playing Billiards , 2015 .
[42] Honglak Lee,et al. Action-Conditional Video Prediction using Deep Networks in Atari Games , 2015, NIPS.
[43] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Roberto Cipolla,et al. Understanding RealWorld Indoor Scenes with Synthetic Data , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Jitendra Malik,et al. Learning Visual Predictive Models of Physics for Playing Billiards , 2015, ICLR.
[46] Ali Farhadi,et al. Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[48] Fei-Fei Li,et al. Deep visual-semantic alignments for generating image descriptions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).