Neural Photo Editing Andrew Brock.

Slides:

Advertisements

Similar presentations

1 Computational Geometry Chapter Range queries How do you efficiently find points that are inside of a rectangle? –Orthogonal range query ([x 1,

Advertisements

These figures correspond to the image using shear =10 pixels And 2D convolution was done in order to get the images Using R=0 y0 Using R=1 y1.

Y A S O O B A L I b o r n o n 1 9 t h F e b r u a r y i n K a n p u r d i s t r i c t o f U t t a r P r a d e s h. H e s t a r t e d s i n g i.

Presenting: Itai Avron Supervisor: Chen Koren Final Presentation Spring 2005 Implementation of Artificial Intelligence System on FPGA.

Lecture 3: CNN: Back-propagation

Spatial Pyramid Pooling in Deep Convolutional

7/6/2015 Orthogonal Functions Chapter /6/2015 Orthogonal Functions Chapter 7 2.

Generic object detection with deformable part-based models

Convolutional Neural Networks for Image Processing with Applications in Mobile Robotics By, Sruthi Moola.

Digital Images Chapter 8 Exploring the Digital Domain.

Creating With Code.

Video Tracking Using Learned Hierarchical Features

Goes to the movies…. Workspace… Capture/Import Video.

Radoslav Forgáč, Igor Mokriš Pulse Coupled Neural Network Models for Dimension Reduction of Classification Space Institute of Informatics Slovak Academy.

Introduction to Related Papers of Vessel Segmentation Methods Advisor : Ku-Yaw Chang Student : Wei-Lu Lin 2015/1/7.

Automatic Screening of Sonar Imagery Using Artificial Intelligence Techniques John Tran.

Convolutional Neural Network

Facial Smile Detection Based on Deep Learning Features Authors: Kaihao Zhang, Yongzhen Huang, Hong Wu and Liang Wang Center for Research on Intelligent.

Sellmysourcecode Perfect Photo Studio App Sourcecod e.

Content Based Coding of Face Images

Facial Detection via Convolutional Neural Network Nathan Schneider.

When deep learning meets object detection: Introduction to two technologies: SSD and YOLO Wenchi Ma.

Generative Adversarial Nets

Convolutional Neural Network

Radoslav Forgáč, Igor Mokriš

DeepFont: Identify Your Font from An Image

Data Mining, Neural Network and Genetic Programming

Introduction to raster graphics

Convolutional Neural Fabrics by Shreyas Saxena, Jakob Verbeek

Textual Video Prediction Week 2

Week III: Deep Tracking

Applications of Deep Learning and how to get started with implementation of deep learning Presentation By : Manaswi Advisor : Dr.Chinmay.

Implementing Boosting and Convolutional Neural Networks For Particle Identification (PID) Khalid Teli .

Hierarchical Deep Convolutional Neural Network

Recovery from Occlusion in Deep Feature Space for Face Recognition

Lecture 5 Smaller Network: CNN

Sujay Yadawadkar, Virginia Tech

Super-Resolution Image Reconstruction

Single Image Super-Resolution

Why PERFORMING BACKGROUND CHECKS on Your TENANTS Can Save Money.

Efficient Deep Model for Monocular Road Segmentation

Authors: Jun-Yan Zhu*, Taesun Park*, Phillip Isola, Alexei A. Efros

Introduction to Neural Networks

Generative and Discriminative Voxel Modeling

Major Parameters Marketing IT

RGB-D Image for Scene Recognition by Jiaqi Guo

Zhengjun Pan and Hamid Bolouri Department of Computer Science

in Advertisements: Part One SB 2.7

GPU Accelerated Image Super-Resolution

Resolution Resolution: 6 x 4.

Generative Adversarial Network

Age and Gender Classification using Convolutional Neural Networks

Deep Neural Networks for Onboard Intelligence

Visualizing and Understanding Convolutional Networks

Lip movement Synthesis from Text

1. Write all that you can about this image around the outside

Where I will take my photos and why this location:

TPGAN overview.

The Image The pixels in the image The mask The resulting image 255 X

Model Compression Joseph E. Gonzalez

Using conventions of real media texts

Department of Electrical Engineering

Object Detection Implementations

Deep screen image crop and enhance

End-to-End Facial Alignment and Recognition

Deep screen image crop and enhance

Recent Developments on Super-Resolution

CRCV REU 2019 Aaron Honculada.

Presentation transcript:

Neural Photo Editing Andrew Brock

Introduction

Background: VAEs

Background: VAEs

Background: GANs

Background: GANs

The IAN Model

Multiscale Dilated Conv Blocks Image credit: http://liangchiehchen.com/fig/deeplab_aspp.jpg

Multiscale Dilated Conv Blocks Expressivity = range of functions a block can represent / number of parameters

Faster Dilation through Reshapes Image credit: Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network, Twitter Cortex

Orthogonality Initializing weights with orthogonal matrices works well…so why not keep them orthogonal?

Orthogonal Regularization Initializing weights with orthognal matrices works well…so why not keep them orthogonal?

Adding Modifications

Photo Editing

Photo Editing

Thanks!