PPT-3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks

Zhaoliang Lun Matheus Gadelha Evangelos Kalogerakis Subhransu Maji Rui Wang Image from Autodesk 3D Maya Creating 3D shapes is not easy Goal 2D line drawings in 3D shapes out ShapeMVD. RECOGNITION. does size matter?. Karen . Simonyan. Andrew . Zisserman. Contents. Why I Care. Introduction. Convolutional Configuration . Classification. Experiments. Conclusion. Big Picture. Why I . care. Non-scanning CT (computerized tomography). Standard CT system. CT(computerized tomography) creates 3D views of what is inside. General medical imaging technique to look inside of a patient’ body. Background. Kuan-Chuan. Peng. Tsuhan. Chen. 1. Introduction. Breakthrough progress in object classification.. 2. O. . Russakovsky. . et al. . ImageNet. . large scale visual recognition challenge. .. . arXiv:1409.0575, 2014.. Many slides adapted from S. Seitz. Multi-view . stereo. Generic problem formulation: given several images of the same object or scene, compute a representation of its 3D shape. Reconstruction (side). Neural . Network Architectures:. f. rom . LeNet. to ResNet. Lana Lazebnik. Figure source: A. . Karpathy. What happened to my field?. . Classification:. . ImageNet. Challenge top-5 error. Figure source: . Non-scanning CT (computerized tomography). Standard CT system. CT(computerized tomography) creates 3D views of what is inside. General medical imaging technique to look inside of a patient’ body. Background. Last time. Linear classifiers on pixels bad, need non-linear classifiers. Multi-layer . perceptrons. . overparametrized. Reduce parameters by local connections and shift invariance => Convolution. Convolutions. Reduce parameters. Capture shift-invariance: location of patch in image should not matter. Subsampling. Allows greater invariance to deformations. Allows the capture of large patterns with small filters. 2D Sketches. 1. 2D Sketches. Profiles:. Closed loop shape that is drawn on a flat 2D plane (referred to as a datum) and is used to create 3D objects.. 2D Profiles consist of:. Points. Lines. Circles. Convolutional Codes COS 463 : Wireless Networks Lecture 9 Kyle Jamieson [Parts adapted from H. Balakrishnan ] So far, we’ve seen block codes Convolutional Codes: Simple design, especially at the transmitter Zan Gao, . Deyu Wang. , Xiangnan He, Hua . Zhang. Tianjin University . of Technology. National University of Singapore. Previous work. Proposed method. Experiments. Conclusion. Outline. Previous work. person. grass. trees. motorbike. road. Evaluation metric. Pixel classification!. Accuracy?. Heavily unbalanced. Common classes are over-emphasized. Intersection over Union. Average across classes and images. Kannan . Neten. Dharan. Introduction . Alzheimer’s Disease is a kind of dementia which is caused by damage to nerve cells in the brain and the usual side effects of it are loss of memory or other cognitive impairments.. By. Neha Ujjainkar & Abhishek Khandekar. Outline. Problem Statement. Introduction. Literature Review. Data set. Significance. Experiment Design. Timeline and Milestones. References. 2. Problem Statement.