23/11 Single image shape estimation [Itamar Talmi & Roey Mechrez]
Chen, Weifeng, Donglai Xiang, and Jia Deng. "Surface Normals in the Wild." arXiv preprint arXiv:1704.02956 (2017).
Chen, Weifeng, et al. "Single-image depth perception in the wild." Advances in Neural Information Processing Systems. 2016.
Roy, Anirban, and Sinisa Todorovic. "Monocular depth estimation using neural regression forest." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
Wang, Xiaolong, David Fouhey, and Abhinav Gupta. "Designing deep networks for surface normal estimation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
Bansal, Aayush, et al. "Pixelnet: Representation of the pixels, by the pixels, and for the pixels." arXiv preprint arXiv:1702.06506(2017).
Kurenkov, Andrey, et al. "DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image." arXiv preprint arXiv:1708.04672 (2017).
30/11 Lighting and Shading [Kfir Shem-Tov]
Thomas, Manu Mathew, and Angus G. Forbes. "Deep Illumination: Approximating Dynamic Global Illumination with Generative Adversarial Network." arXiv preprint arXiv:1710.09834 (2017)
Wehrwein, Scott, Kavita Bala, and Noah Snavely. "Shadow detection and sun direction in photo collections." 2015 IEEE International Conference on 3D Vision (3DV), 2015
Schied, Christoph, et al. "Spatiotemporal variance-guided filtering: real-time reconstruction for path-traced global illumination." Proceedings of High Performance Graphics. ACM, 2017
Liu, Guilin, et al. "Material Editing Using a Physically Based Rendering Network." arXiv preprint arXiv:1708.00106 (2017)
7/12 Material recognition with shape [Yoni Chechik & Reut Azaria]
Zhao, Cheng, Li Sun, and Rustam Stolkin. "A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition." arXiv preprint arXiv:1703.04699 (2017).
DeGol, Joseph, Mani Golparvar-Fard, and Derek Hoiem. "Geometry-Informed Material Recognition." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
Tanaka, Kenichiro, et al. "Material Classification using Frequency-and Depth-Dependent Time-of-Flight Distortion." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017.
Su, Shuochen, et al. "Material classification using raw time-of-flight measurements." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
14/12 Material recognition [Ori Bryt & Mordecai Sayag]
Zhang, Hang, Kristin Dana, and Ko Nishino. "Reflectance hashing for material recognition." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
Bell, Sean, et al. "Material recognition in the wild with the materials in context database." Proceedings of the IEEE conference on computer vision and pattern recognition. 2015.
Wang, Ting-Chun, et al. "A 4D light-field dataset and CNN architectures for material recognition." European Conference on Computer Vision. Springer International Publishing, 2016.
Xue, Jia, et al. "Differential angular imaging for material recognition." arXiv preprint arXiv:1612.02372 (2016).
Georgoulis, Stamatios, et al. "Material Classification under Natural Illumination Using Reflectance Maps." Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on. IEEE, 2017.
21/12 ----- no class - Hanukkah -----
28/12 Model Driven 3D reconstruction [Ohad Shelly & Alon Shoshan]
Sankar, Aditya, and Steven M. Seitz. "In situ CAD capture." MobileHCI. 2016.
Liu, Zicheng, et al. "Model-driven indoor scenes modeling from a single image." Proceedings of the 41st Graphics Interface Conference. Canadian Information Processing Society, 2015.
Satkin, Scott, et al. "3dnn: 3d nearest neighbor." International Journal of Computer Vision 111.1 (2015): 69-97.
Izadinia, Hamid, Qi Shan, and Steven M. Seitz. "IM2CAD." arXiv preprint arXiv:1608.05137 (2016).
4/1 Predicting forces and dynamics [Nadav Arbel & Ran Ben Izhak]
Mottaghi, Roozbeh, et al. "“What happens if...” Learning to Predict the Effect of Forces in Images." European Conference on Computer Vision. Springer International Publishing, 2016.
Agrawal, Pulkit, et al. "Learning to poke by poking: Experiential learning of intuitive physics." Advances in Neural Information Processing Systems. 2016.
Mottaghi, Roozbeh, et al. "Newtonian scene understanding: Unfolding the dynamics of objects in static images." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
Finn, Chelsea, Ian Goodfellow, and Sergey Levine. "Unsupervised learning for physical interaction through video prediction." Advances in Neural Information Processing Systems. 2016.
Fragkiadaki, Katerina, et al. "Learning visual predictive models of physics for playing billiards." arXiv preprint arXiv:1511.07404(2015).
Soo Park, Hyun, and Jianbo Shi. "Force from motion: decoding physical sensation in a first person video." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016.
11/1 Elastic shape recovery [Yair Herbst & Adam Wolff]
Yang, Shan, and Ming C. Lin. "MaterialCloning: Acquiring Elasticity Parameters from Images for Medical Applications." IEEE transactions on visualization and computer graphics 22.9 (2016): 2122-2135.
Malti, Abed, and Cédric Herzet. "Elastic Shape-from-Template with Spatially Sparse Deforming Forces." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017.
Haouchine, Nazim, and Stéphane Cotin. "Template-based Monocular 3D Recovery of Elastic Shapes using Lagrangian Multipliers." Computer Vision and Pattern Recognition (CVPR). 2017.
Kanazawa, Angjoo, et al. "Learning 3D Articulation and Deformation using 2D Images." CoRR (2015).
18/1 SLAM [Adam Geva & Ori Nizan]
Newcombe, Richard A., Dieter Fox, and Steven M. Seitz. "Dynamicfusion: Reconstruction and tracking of non-rigid scenes in real-time." Proceedings of the IEEE conference on computer vision and pattern recognition. 2015.
Whelan, Thomas, et al. "ElasticFusion: Real-time dense SLAM and light source estimation." The International Journal of Robotics Research 35.14 (2016): 1697-1716.
Mur-Artal, Raul, and Juan D. Tardós. "Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras." IEEE Transactions on Robotics 33.5 (2017): 1255-1262.
Pascoe, Geoffrey, et al. "NID-SLAM: Robust Monocular SLAM using Normalised Information Distance." Comput. Vis. Pattern Recognit. 2017.
Chai, Menglei, et al. "Autohair: Fully automatic hair modeling from a single image." ACM Transactions on Graphics (TOG) 35.4 (2016): 116.
Hu, Liwen, et al. "Capturing braided hairstyles." ACM Transactions on Graphics (TOG) 33.6 (2014): 225.
Hu, Liwen, et al. "Single-view hair modeling using a hairstyle database." ACM Transactions on Graphics (TOG) 34.4 (2015): 125.
Garment recovery from a single image
Casati, Romain, Gilles Daviet, and Florence Bertails-Descoubes. Inverse Elastic Cloth Design with Contact and Friction. Diss. Inria Grenoble Rhône-Alpes, Université de Grenoble, 2016.
Yang, Shan, et al. "Detailed garment recovery from a single-view image." arXiv preprint arXiv:1608.01250 (2016).
Zhou, Bin, et al. "Garment modeling from a single image." Computer graphics forum. Vol. 32. No. 7. 2013.
Jeong, Moon‐Hwan, Dong‐Hoon Han, and Hyeong‐Seok Ko. "Garment capture from a photograph." Computer Animation and Virtual Worlds 26.3-4 (2015): 291-300.
Yang, Shan, Junbang Liang, and Ming C. Lin. "Learning-Based Cloth Material Recovery From Video." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2017.
Daněřek, R., et al. "DeepGarment: 3D Garment Shape Estimation from a Single Image." Computer Graphics Forum. Vol. 36. No. 2. 2017.
Estimation of physical properties
Mottaghi, Roozbeh, et al. "See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content." arXiv preprint arXiv:1701.02718 (2017).
Wu, Jiajun, et al. "Physics 101: Learning Physical Object Properties from Unlabeled Videos." BMVC. 2016.
Wu, Jiajun, et al. "Galileo: Perceiving physical object properties by integrating a physics engine with deep learning." Advances in neural information processing systems. 2015.
Yuan, Wenzhen, et al. "Connecting Look and Feel: Associating the visual and tactile properties of physical materials." arXiv preprint arXiv:1704.03822 (2017).
Zhang, Hang, Kristin Dana, and Ko Nishino. "Friction from reflectance: Deep reflectance codes for predicting physical surface properties from one-shot in-field reflectance." European Conference on Computer Vision. Springer International Publishing, 2016.