Publications

    Jiajun Wu

  • Renqiao Zhang, Jiajun Wu, Chengkai Zhang, William T. Freeman, Joshua B. Tenenbaum:
    A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding (web) (bibtex)
    Proceedings of the 38th Annual Conference of the Cognitive Science Society
    #intuitive physics, #simulation, #deep learning, #scene understanding
    @article{RenqiaoZhang:2016:84ee7,
    author = {Renqiao Zhang and Jiajun Wu and Chengkai Zhang and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Proceedings of the 38th Annual Conference of the Cognitive Science Society},
    title = {A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding},
    year = {2016},
    keywords = {intuitive physics, simulation, deep learning, scene understanding},
    doi = {},
    url = {http://blocks.csail.mit.edu/}
    }
  • Jiajun Wu, Joseph J. Lim, Hongyi Zhang, Joshua B. Tenenbaum, William T. Freeman:
    Physics 101: Learning Physical Object Properties from Unlabeled Videos (web) (bibtex)
    British Machine Vision Conference (BMVC)
    #intuitive physics, #unsupervised learning, #deep learning, #scene understanding
    @article{JiajunWu:2016:9e6c9,
    author = {Jiajun Wu and Joseph J. Lim and Hongyi Zhang and Joshua B. Tenenbaum and William T. Freeman},
    journal = {British Machine Vision Conference (BMVC)},
    title = {Physics 101: Learning Physical Object Properties from Unlabeled Videos},
    year = {2016},
    keywords = {intuitive physics, unsupervised learning, deep learning, scene understanding},
    doi = {},
    url = {http://phys101.csail.mit.edu/}
    }
  • Jiajun Wu, Ilker Yildirim, Joseph J. Lim, William T. Freeman, Joshua B. Tenenbaum:
    Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #intuitive physics, #simulation, #deep learning, #unsupervised learning, #scene understanding
    @article{JiajunWu:2015:27dc4,
    author = {Jiajun Wu and Ilker Yildirim and Joseph J. Lim and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning},
    year = {2015},
    keywords = {intuitive physics, simulation, deep learning, unsupervised learning, scene understanding},
    doi = {},
    url = {http://galileo.csail.mit.edu/}
    }
  • Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
    Single Image 3D Interpreter Network (web) (bibtex)
    European Conference in Computer Vision (ECCV)
    #deep learning, #self-supervised learning, #3d vision
    @article{JiajunWu:2016:770f7,
    author = {Jiajun Wu and Tianfan Xue and Joseph J. Lim and Yuandong Tian and Joshua B. Tenenbaum and Antonio Torralba and William T. Freeman},
    journal = {European Conference in Computer Vision (ECCV)},
    title = {Single Image 3D Interpreter Network},
    year = {2016},
    keywords = {deep learning, self-supervised learning, 3d vision},
    doi = {},
    url = {http://3dinterpreter.csail.mit.edu/}
    }
  • Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T. Freeman, Joshua B. Tenenbaum:
    Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #simulation, #deep learning, #generative adversarial learning, #3d vision
    @article{JiajunWu:2016:3471d,
    author = {Jiajun Wu and Chengkai Zhang and Tianfan Xue and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling},
    year = {2016},
    keywords = {simulation, deep learning, generative adversarial learning, 3d vision},
    doi = {},
    url = {http://3dgan.csail.mit.edu/}
    }
  • Zhoutong Zhang, Jiajun Wu, Qiujia Li, Zhengjia Huang, James Traer, Josh H. McDermott, Joshua B. Tenenbaum, William T. Freeman:
    Generative Modeling of Audible Shapes for Object Perception (pdf) (bibtex)
    IEEE International Conference on Computer Vision (ICCV)
    #deep learning, #simulation, #auditory perception, #scene understanding
    @article{ZhoutongZhang:2017:4f1fd,
    author = {Zhoutong Zhang and Jiajun Wu and Qiujia Li and Zhengjia Huang and James Traer and Josh H. McDermott and Joshua B. Tenenbaum and William T. Freeman},
    journal = {IEEE International Conference on Computer Vision (ICCV)},
    title = {Generative Modeling of Audible Shapes for Object Perception},
    year = {2017},
    keywords = {deep learning, simulation, auditory perception, scene understanding},
    doi = {},
    url = {https://jiajunwu.com/papers/gensound_iccv.pdf}
    }
  • Jiajun Wu, Joshua B. Tenenbaum, Pushmeet Kohli:
    Neural Scene De-rendering (web) (bibtex)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    #deep learning, #self-supervised learning, #inverse graphics, #computer vision, #scene understanding
    @article{JiajunWu:2017:2afa9,
    author = {Jiajun Wu and Joshua B. Tenenbaum and Pushmeet Kohli},
    journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {Neural Scene De-rendering},
    year = {2017},
    keywords = {deep learning, self-supervised learning, inverse graphics, computer vision, scene understanding},
    doi = {},
    url = {http://nsd.csail.mit.edu/}
    }
  • Jiajun Wu, Erika Lu, Pushmeet Kohli, William T. Freeman, Joshua B. Tenenbaum:
    Learning to See Physics via Visual De-animation (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #intuitive physics, #simulation, #deep learning, #scene understanding
    @article{JiajunWu:2017:4849f,
    author = {Jiajun Wu and Erika Lu and Pushmeet Kohli and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Learning to See Physics via Visual De-animation},
    year = {2017},
    keywords = {intuitive physics, simulation, deep learning, scene understanding},
    doi = {},
    url = {http://vda.csail.mit.edu/}
    }
  • Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, William T. Freeman, Joshua B. Tenenbaum:
    MarrNet: 3D Shape Reconstruction via 2.5D Sketches (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #3d vision, #deep learning
    @article{JiajunWu:2017:cfe2b,
    author = {Jiajun Wu and Yifan Wang and Tianfan Xue and Xingyuan Sun and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {MarrNet: 3D Shape Reconstruction via 2.5D Sketches},
    year = {2017},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://marrnet.csail.mit.edu/}
    }
  • Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Joshua B. Tenenbaum:
    Self-Supervised Intrinsic Image Decomposition (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #computer vision, #deep learning, #self-supervised learning
    @article{MichaelJanner:2017:e02af,
    author = {Michael Janner and Jiajun Wu and Tejas D. Kulkarni and Ilker Yildirim and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Self-Supervised Intrinsic Image Decomposition},
    year = {2017},
    keywords = {computer vision, deep learning, self-supervised learning},
    doi = {},
    url = {http://rin.csail.mit.edu/}
    }
  • Zhoutong Zhang, Qiujia Li, Zhengjia Huang, Jiajun Wu, Joshua B. Tenenbaum, William T. Freeman:
    Shape and Material from Sound (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #auditory perception, #deep learning, #simulation
    @article{ZhoutongZhang:2017:1d3c7,
    author = {Zhoutong Zhang and Qiujia Li and Zhengjia Huang and Jiajun Wu and Joshua B. Tenenbaum and William T. Freeman},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Shape and Material from Sound},
    year = {2017},
    keywords = {auditory perception, deep learning, simulation},
    doi = {},
    url = {http://sound.csail.mit.edu/}
    }
  • Xingyuan Sun, Jiajun Wu, Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, Tianfan Xue, Joshua B. Tenenbaum, William T. Freeman:
    Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling (web) (bibtex)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    #3d vision, #deep learning
    @article{XingyuanSun:2018:02ad6,
    author = {Xingyuan Sun and Jiajun Wu and Xiuming Zhang and Zhoutong Zhang and Chengkai Zhang and Tianfan Xue and Joshua B. Tenenbaum and William T. Freeman},
    journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling},
    year = {2018},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://pix3d.csail.mit.edu}
    }
  • David Zheng, Vinson Luo, Jiajun Wu, Joshua B. Tenenbaum:
    Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks (web) (bibtex)
    Conference on Uncertainty in Artificial Intelligence (UAI)
    #intuitive physics, #scene understanding, #graph networks
    @article{DavidZheng:2018:91c7a,
    author = {David Zheng and Vinson Luo and Jiajun Wu and Joshua B. Tenenbaum},
    journal = {Conference on Uncertainty in Artificial Intelligence (UAI)},
    title = {Unsupervised Learning of Latent Physical Properties Using Perception-Prediction Networks},
    year = {2018},
    keywords = {intuitive physics, scene understanding, graph networks},
    doi = {},
    url = {http://ppn.csail.mit.edu}
    }
  • Shaoxiong Wang, Jiajun Wu, Xingyuan Sun, Wenzhen Yuan, William T. Freeman, Joshua B. Tenenbaum, Edward H. Adelson:
    3D Shape Perception from Monocular Vision, Touch, and Shape Priors (web) (bibtex)
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    #3d vision, #multi-modal learning, #deep learning
    @article{ShaoxiongWang:2018:158c4,
    author = {Shaoxiong Wang and Jiajun Wu and Xingyuan Sun and Wenzhen Yuan and William T. Freeman and Joshua B. Tenenbaum and Edward H. Adelson},
    journal = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    title = {3D Shape Perception from Monocular Vision, Touch, and Shape Priors},
    year = {2018},
    keywords = {3d vision, multi-modal learning, deep learning},
    doi = {},
    url = {http://touch.csail.mit.edu}
    }
  • Anurag Ajay, Jiajun Wu, Nima Fazeli, Maria Bauza, Leslie P. Kaelbling, Joshua B. Tenenbaum, Alberto Rodriguez:
    Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing (web) (bibtex)
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
    #dynamics modeling, #deep learning, #robotics
    @article{AnuragAjay:2018:2ddc2,
    author = {Anurag Ajay and Jiajun Wu and Nima Fazeli and Maria Bauza and Leslie P. Kaelbling and Joshua B. Tenenbaum and Alberto Rodriguez},
    journal = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
    title = {Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing},
    year = {2018},
    keywords = {dynamics modeling, deep learning, robotics},
    doi = {},
    url = {http://physplus.csail.mit.edu}
    }
  • Tianfan Xue, Jiajun Wu, Zhoutong Zhang, Chengkai Zhang, Joshua B. Tenenbaum, William T. Freeman:
    Seeing Tree Structure from Vibration (web) (bibtex)
    European Conference on Computer Vision (ECCV)
    #computer vision, #hierarchical bayes, #scene understanding
    @article{TianfanXue:2018:4ccba,
    author = {Tianfan Xue and Jiajun Wu and Zhoutong Zhang and Chengkai Zhang and Joshua B. Tenenbaum and William T. Freeman},
    journal = {European Conference on Computer Vision (ECCV)},
    title = {Seeing Tree Structure from Vibration},
    year = {2018},
    keywords = {computer vision, hierarchical bayes, scene understanding},
    doi = {},
    url = {http://tree.csail.mit.edu/}
    }
  • Jiajun Wu, Chengkai Zhang, Xiuming Zhang, Zhoutong Zhang, William T. Freeman, Joshua B. Tenenbaum:
    Learning Shape Priors for Single-View 3D Completion and Reconstruction (web) (bibtex)
    European Conference on Computer Vision (ECCV)
    #3d vision, #deep learning
    @article{JiajunWu:2018:11782,
    author = {Jiajun Wu and Chengkai Zhang and Xiuming Zhang and Zhoutong Zhang and William T. Freeman and Joshua B. Tenenbaum},
    journal = {European Conference on Computer Vision (ECCV)},
    title = {Learning Shape Priors for Single-View 3D Completion and Reconstruction},
    year = {2018},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://shapehd.csail.mit.edu/}
    }
  • Zhijian Liu, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Physical Primitive Decomposition (web) (bibtex)
    European Conference on Computer Vision (ECCV)
    #3d vision, #deep learning, #intuitive physics
    @article{ZhijianLiu:2018:7414d,
    author = {Zhijian Liu and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {European Conference on Computer Vision (ECCV)},
    title = {Physical Primitive Decomposition},
    year = {2018},
    keywords = {3d vision, deep learning, intuitive physics},
    doi = {},
    url = {http://ppd.csail.mit.edu/}
    }
  • Jiajun Wu, Tianfan Xue, Joseph J. Lim, Yuandong Tian, Joshua B. Tenenbaum, Antonio Torralba, William T. Freeman:
    3D Interpreter Networks for Viewer-Centered Wireframe Modeling (web) (bibtex)
    International Journal of Computer Vision (IJCV)
    #3d vision, #deep learning
    @article{JiajunWu:2018:ad749,
    author = {Jiajun Wu and Tianfan Xue and Joseph J. Lim and Yuandong Tian and Joshua B. Tenenbaum and Antonio Torralba and William T. Freeman},
    journal = {International Journal of Computer Vision (IJCV)},
    title = {3D Interpreter Networks for Viewer-Centered Wireframe Modeling},
    year = {2018},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://3dinterpreter.csail.mit.edu/}
    }
  • Ilker Yildirim, Kevin Smith, Mario Belledonne, Jiajun Wu, Joshua B. Tenenbaum:
    Neurocomputational Modeling of Human Physical Scene Understanding (pdf) (bibtex)
    Conference on Cognitive Computational Neuroscience (CCN)
    #intuitive physics, #deep learning, #scene understanding
    @article{IlkerYildirim:2018:068cb,
    author = {Ilker Yildirim and Kevin Smith and Mario Belledonne and Jiajun Wu and Joshua B. Tenenbaum},
    journal = {Conference on Cognitive Computational Neuroscience (CCN)},
    title = {Neurocomputational Modeling of Human Physical Scene Understanding},
    year = {2018},
    keywords = {intuitive physics, deep learning, scene understanding},
    doi = {},
    url = {https://jiajunwu.com/papers/humanphys_ccn.pdf}
    }
  • Amir Arsalan Soltani, Haibin Huang, Jiajun Wu, Tejas D Kulkarni, Joshua B Tenenbaum:
    Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative (web) (doi) (bibtex)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    #2d to 3d, #3d vision, #3d generation, #3d reconstruction, #inverse vision, #scene understanding, #deep learning
    @article{AmirArsalanSoltani:2017:4a1d2,
    author = {Amir Arsalan Soltani and Haibin Huang and Jiajun Wu and Tejas D Kulkarni and Joshua B Tenenbaum},
    journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative },
    year = {2017},
    keywords = {2d to 3d, 3d vision, 3d generation, 3d reconstruction, inverse vision, scene understanding, deep learning},
    doi = {10.1109/CVPR.2017.269},
    url = {https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil}
    }
  • Shunyu Yao, Tzu-Ming Harry Hsu, Jun-Yan Zhu, Jiajun Wu, Antonio Torralba, William T. Freeman, Joshua B. Tenenbaum:
    3D-Aware Scene Manipulation via Inverse Graphics (web) (bibtex)
    Advances in Neural Information Processing Systems (NeurIPS)
    #3d vision, #deep learning, #scene understanding
    @article{ShunyuYao:2018:a9aef,
    author = {Shunyu Yao and Tzu-Ming Harry Hsu and Jun-Yan Zhu and Jiajun Wu and Antonio Torralba and William T. Freeman and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {3D-Aware Scene Manipulation via Inverse Graphics},
    year = {2018},
    keywords = {3d vision, deep learning, scene understanding},
    doi = {},
    url = {http://3dsdn.csail.mit.edu/}
    }
  • Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Learning to Exploit Stability for 3D Scene Parsing (web) (bibtex)
    Advances in Neural Information Processing Systems (NeurIPS)
    #3d vision, #deep learning, #scene understanding
    @article{YilunDu:2018:b73f5,
    author = {Yilun Du and Zhijian Liu and Hector Basevi and Ales Leonardis and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Learning to Exploit Stability for 3D Scene Parsing},
    year = {2018},
    keywords = {3d vision, deep learning, scene understanding},
    doi = {},
    url = {http://scenephys.csail.mit.edu/}
    }
  • Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Learning to Reconstruct Shapes from Unseen Classes (web) (bibtex)
    Advances in Neural Information Processing Systems (NeurIPS)
    #3d vision, #deep learning
    @article{XiumingZhang:2018:0b69d,
    author = {Xiuming Zhang and Zhoutong Zhang and Chengkai Zhang and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Learning to Reconstruct Shapes from Unseen Classes},
    year = {2018},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://genre.csail.mit.edu/}
    }
  • Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, Joshua B. Tenenbaum:
    Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding (web) (bibtex)
    Advances in Neural Information Processing Systems (NeurIPS)
    #visual reasoning, #deep learning, #scene understanding
    @article{KexinYi:2018:18b7f,
    author = {Kexin Yi and Jiajun Wu and Chuang Gan and Antonio Torralba and Pushmeet Kohli and Joshua B. Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding},
    year = {2018},
    keywords = {visual reasoning, deep learning, scene understanding},
    doi = {},
    url = {http://nsvqa.csail.mit.edu/}
    }
  • Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Joshua B. Tenenbaum, William T. Freeman:
    Visual Object Networks: Image Generation with Disentangled 3D Representations (web) (bibtex)
    Advances in Neural Information Processing Systems (NeurIPS)
    #3d vision, #deep learning
    @article{Jun-YanZhu:2018:3aa73,
    author = {Jun-Yan Zhu and Zhoutong Zhang and Chengkai Zhang and Jiajun Wu and Antonio Torralba and Joshua B. Tenenbaum and William T. Freeman},
    journal = {Advances in Neural Information Processing Systems (NeurIPS)},
    title = {Visual Object Networks: Image Generation with Disentangled 3D Representations},
    year = {2018},
    keywords = {3d vision, deep learning},
    doi = {},
    url = {http://von.csail.mit.edu/}
    }
  • Anurag Ajay, Maria Bauza, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie P. Kaelbling:
    Combining Physical Simulators and Object-Based Networks for Control (web) (bibtex)
    IEEE International Conference on Robotics and Automation (ICRA)
    #dynamics modeling, #deep learning, #robotics
    @article{AnuragAjay:2019:95128,
    author = {Anurag Ajay and Maria Bauza and Jiajun Wu and Nima Fazeli and Joshua B. Tenenbaum and Alberto Rodriguez and Leslie P. Kaelbling},
    journal = {IEEE International Conference on Robotics and Automation (ICRA)},
    title = {Combining Physical Simulators and Object-Based Networks for Control},
    year = {2019},
    keywords = {dynamics modeling, deep learning, robotics},
    doi = {},
    url = {http://sain.csail.mit.edu/}
    }
  • Yunzhu Li, Jiajun Wu, Jun-Yan Zhu, Antonio Torralba, Joshua B. Tenenbaum, Russ Tedrake:
    Propagation Networks for Model-Based Control Under Partial Observation (web) (bibtex)
    IEEE International Conference on Robotics and Automation (ICRA)
    #dynamics modeling, #deep learning, #robotics
    @article{YunzhuLi:2019:dfe34,
    author = {Yunzhu Li and Jiajun Wu and Jun-Yan Zhu and Antonio Torralba and Joshua B. Tenenbaum and Russ Tedrake},
    journal = {IEEE International Conference on Robotics and Automation (ICRA)},
    title = {Propagation Networks for Model-Based Control Under Partial Observation},
    year = {2019},
    keywords = {dynamics modeling, deep learning, robotics},
    doi = {},
    url = {http://propnet.csail.mit.edu/}
    }
  • Yuanming Hu, Jiancheng Liu, Andrew Spielberg, Joshua B. Tenenbaum, William T. Freeman, Jiajun Wu, Daniela Rus, Wojciech Matusik:
    ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics (web) (bibtex)
    IEEE International Conference on Robotics and Automation (ICRA)
    #dynamics modeling, #deep learning, #robotics
    @article{YuanmingHu:2019:88b13,
    author = {Yuanming Hu and Jiancheng Liu and Andrew Spielberg and Joshua B. Tenenbaum and William T. Freeman and Jiajun Wu and Daniela Rus and Wojciech Matusik},
    journal = {IEEE International Conference on Robotics and Automation (ICRA)},
    title = {ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics},
    year = {2019},
    keywords = {dynamics modeling, deep learning, robotics},
    doi = {},
    url = {https://github.com/yuanming-hu/ChainQueen}
    }
  • Ilker Yildirim, Jiajun Wu, Nancy Kanwisher, Joshua B. Tenenbaum:
    An Integrative Computational Architecture for Object-Driven Cortex (web) (bibtex)
    Current Opinion in Neurobiology (CONEUR)
    #computational neuroscience, #object representation
    @article{IlkerYildirim:2019:443ba,
    author = {Ilker Yildirim and Jiajun Wu and Nancy Kanwisher and Joshua B. Tenenbaum},
    journal = {Current Opinion in Neurobiology (CONEUR)},
    title = {An Integrative Computational Architecture for Object-Driven Cortex},
    year = {2019},
    keywords = {computational neuroscience, object representation},
    doi = {},
    url = {https://www.sciencedirect.com/science/article/pii/S0959438818301995}
    }
  • Nima Fazeli, Miquel Oller, Jiajun Wu, Zheng Wu, Joshua B. Tenenbaum, Alberto Rodriguez:
    See, Feel, Act: Hierarchical Learning for Complex Manipulation Skills with Multi-sensory Fusion (web) (bibtex)
    Science Robotics
    #robotics, #deep learning, #dynamics modeling, #manipulation
    @article{NimaFazeli:2019:a5ddd,
    author = {Nima Fazeli and Miquel Oller and Jiajun Wu and Zheng Wu and Joshua B. Tenenbaum and Alberto Rodriguez},
    journal = {Science Robotics},
    title = {See, Feel, Act: Hierarchical Learning for Complex Manipulation Skills with Multi-sensory Fusion},
    year = {2019},
    keywords = {robotics, deep learning, dynamics modeling, manipulation},
    doi = {},
    url = {http://robotics.sciencemag.org/content/4/26/eaav3123}
    }
  • Sidi Lu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu:
    Neurally-Guided Structure Inference (web) (bibtex)
    International Conference on Machine Learning (ICML)
    #machine learning, #compositionality
    @article{SidiLu:2019:1adc0,
    author = {Sidi Lu and Jiayuan Mao and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {International Conference on Machine Learning (ICML)},
    title = {Neurally-Guided Structure Inference},
    year = {2019},
    keywords = {machine learning, compositionality},
    doi = {},
    url = {http://ngsi.csail.mit.edu/}
    }
  • Zhenjia Xu, Jiajun Wu, Andy Zeng, Joshua B. Tenenbaum, Shuran Song:
    DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions (web) (bibtex)
    Robotics: Science and Systems (RSS)
    #deep learning, #robotics, #intuitive physics
    @article{ZhenjiaXu:2019:b51cb,
    author = {Zhenjia Xu and Jiajun Wu and Andy Zeng and Joshua B. Tenenbaum and Shuran Song},
    journal = {Robotics: Science and Systems (RSS)},
    title = {DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions},
    year = {2019},
    keywords = {deep learning, robotics, intuitive physics},
    doi = {},
    url = {http://www.zhenjiaxu.com/DensePhysNet/}
    }
  • Yunyun Wang, Chuang Gan, Max H. Siegel, Zhoutong Zhang, Jiajun Wu, Joshua B. Tenenbaum:
    A Computational Model for Combinatorial Generalization in Physical Perception from Sound (pdf) (bibtex)
    Conference on Cognitive Computational Neuroscience (CCN)
    #auditory scene analysis, #deep learning, #compositionality
    @article{YunyunWang:2019:5e228,
    author = {Yunyun Wang and Chuang Gan and Max H. Siegel and Zhoutong Zhang and Jiajun Wu and Joshua B. Tenenbaum},
    journal = {Conference on Cognitive Computational Neuroscience (CCN)},
    title = {A Computational Model for Combinatorial Generalization in Physical Perception from Sound},
    year = {2019},
    keywords = {auditory scene analysis, deep learning, compositionality},
    doi = {},
    url = {https://jiajunwu.com/papers/combsound_ccn.pdf}
    }
  • Yunzhu Li, Jiajun Wu, Russ Tedrake, Joshua B. Tenenbaum, Antonio Torralba:
    Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, Fluids (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #dynamics predicting, #planning and control
    @article{YunzhuLi:2019:bda8a,
    author = {Yunzhu Li and Jiajun Wu and Russ Tedrake and Joshua B. Tenenbaum and Antonio Torralba},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, Fluids},
    year = {2019},
    keywords = {dynamics predicting, planning and control},
    doi = {},
    url = {http://dpi.csail.mit.edu/}
    }
  • Yunchao Liu, Zheng Wu, Daniel Ritchie, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Learning to Describe Scenes with Programs (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #neuro-symbolic algorithms, #computer vision, #scene understanding
    @article{YunchaoLiu:2019:11ea4,
    author = {Yunchao Liu and Zheng Wu and Daniel Ritchie and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Learning to Describe Scenes with Programs},
    year = {2019},
    keywords = {neuro-symbolic algorithms, computer vision, scene understanding},
    doi = {},
    url = {https://openreview.net/pdf?id=SyNPk2R9K7}
    }
  • Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Learning to Infer and Execute 3D Shape Programs (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #neuro-symbolic algorithms, #shape modeling, #computer vision
    @article{YonglongTian:2019:d433c,
    author = {Yonglong Tian and Andrew Luo and Xingyuan Sun and Kevin Ellis and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Learning to Infer and Execute 3D Shape Programs},
    year = {2019},
    keywords = {neuro-symbolic algorithms, shape modeling, computer vision},
    doi = {},
    url = {http://shape2prog.csail.mit.edu}
    }
  • Chen Sun, Per Karlsson, Jiajun Wu, Joshua B. Tenenbaum, Kevin Murphy:
    Stochastic Prediction of Multi-Agent Interactions from Partial Observations (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #dynamics prediction
    @article{ChenSun:2019:6f938,
    author = {Chen Sun and Per Karlsson and Jiajun Wu and Joshua B. Tenenbaum and Kevin Murphy},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Stochastic Prediction of Multi-Agent Interactions from Partial Observations},
    year = {2019},
    keywords = {dynamics prediction},
    doi = {},
    url = {https://openreview.net/pdf?id=r1xdH3CcKX}
    }
  • Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, Jiajun Wu:
    Reasoning About Physical Interactions with Object-Oriented Prediction and Planning (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #computer vision, #dynamics prediction, #planning
    @article{MichaelJanner:2019:572c1,
    author = {Michael Janner and Sergey Levine and William T. Freeman and Joshua B. Tenenbaum and Chelsea Finn and Jiajun Wu},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Reasoning About Physical Interactions with Object-Oriented Prediction and Planning},
    year = {2019},
    keywords = {computer vision, dynamics prediction, planning},
    doi = {},
    url = {https://people.eecs.berkeley.edu/~janner/o2p2/}
    }
  • Jiayuan Mao, Chuang Gan, Pushmeet Kohli, Joshua B. Tenenbaum, Jiajun Wu:
    The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, Sentences From Natural Supervision (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #computer vision, #visual reasoning, #neuro-symbolic algorithms
    @article{JiayuanMao:2019:208a5,
    author = {Jiayuan Mao and Chuang Gan and Pushmeet Kohli and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, Sentences From Natural Supervision},
    year = {2019},
    keywords = {computer vision, visual reasoning, neuro-symbolic algorithms},
    doi = {},
    url = {http://nscl.csail.mit.edu}
    }
  • Zhenjia Xu, Zhijian Liu, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Unsupervised Discovery of Parts, Structure, and Dynamics (web) (bibtex)
    International Conference on Learning Representations (ICLR)
    #dynamics prediction, #computer vision
    @article{ZhenjiaXu:2019:4110f,
    author = {Zhenjia Xu and Zhijian Liu and Chen Sun and Kevin Murphy and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {International Conference on Learning Representations (ICLR)},
    title = {Unsupervised Discovery of Parts, Structure, and Dynamics},
    year = {2019},
    keywords = {dynamics prediction, computer vision},
    doi = {},
    url = {http://psd.csail.mit.edu}
    }
  • Jiayuan Mao, Xiuming Zhang, Yikai Li, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Program-Guided Image Manipulators (bibtex)
    IEEE International Conference on Computer Vision (ICCV)
    #neuro-symbolic algorithms, #deep learning, #computer vision
    @article{JiayuanMao:2019:a60ea,
    author = {Jiayuan Mao and Xiuming Zhang and Yikai Li and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = { IEEE International Conference on Computer Vision (ICCV)},
    title = {Program-Guided Image Manipulators},
    year = {2019},
    keywords = {neuro-symbolic algorithms, deep learning, computer vision},
    doi = {},
    url = {}
    }
  • Yikai Li*, Jiayuan Mao*, Xiuming Zhang, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
    Perspective Plane Program Induction from a Single Image (web) (bibtex)
    Conference on Computer Vision and Pattern Recognition (CVPR)
    #inverse graphics, #image manipulation
    @article{YikaiLi*:2020:8acd2,
    author = {Yikai Li* and Jiayuan Mao* and Xiuming Zhang and William T. Freeman and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {Perspective Plane Program Induction from a Single Image},
    year = {2020},
    keywords = {inverse graphics, image manipulation},
    doi = {},
    url = {https://arxiv.org/abs/2006.14708}
    }
  • Chi Han*, Jiayuan Mao*, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu:
    Visual Concept-Metaconcept Learning (web) (bibtex)
    Advances in Neural Information Processing Systems
    #language, #concept learning
    @article{ChiHan*:2019:3cbf4,
    author = {Chi Han* and Jiayuan Mao* and Chuang Gan and Joshua B. Tenenbaum and Jiajun Wu},
    journal = {Advances in Neural Information Processing Systems},
    title = {Visual Concept-Metaconcept Learning},
    year = {2019},
    keywords = {language, concept learning},
    doi = {},
    url = {https://arxiv.org/abs/2002.01464}
    }

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