Schedule

Reading List:

• Szeliski Book, Chapters 3.1, 3.2, and 3.5
• Color Transfer between Images
• Non-rigid dense correspondence with applications for image enhancement

Reading list:

• Szeliski Book, Chapter 3.6
• Image Deformation using Moving Least Squares, Schaefer et al. in TOG, 2006

Reading list:

• Poisson Image Editing, Pérez et al. in SIGGRAPH, 2003
• Scene Completion using Millions of Photographs, Hays et al. in TOG, 2007
• CG2Real: Improving the Realism of Computer Generated Images using a Large Collection of Photographs, Johnson et al. in TVCG, 2010
• Modeling the shape of the scene: A holistic representation of the spatial envelope, Oliva et al. in IJCV, 2001
• Semantic photo synthesis, Johnson et al. in Computer Graphics Forum, 2006
• Sketch2Photo: internet image montage, Chen et al. in SIGGRAPHA, 2019
• Photo Clip Art, Lalonde et al. in SIGGRAPH, 2007
• ShadowDraw: Real-Time User Guidance for Freehand Drawing, Lee et al. in TOG, 2011
• AverageExplorer: Interactive Exploration and Alignment of Visual Data Collections, Zhu et al. in SIGGRAPH, 2014

Reading list:

• Joint Bilateral Upsampling, 2007, presented by Jason Xu and Joyce Zhang
• Seam Carving for Content-Aware Image Resizing, Avidan et al. in SIGGRAPH, 2007, presented by Emma Liu
• Interactive Digital Photomontage, Agarwala et al. in SIGGRAPH, 2004
• GrabCut -Interactive Foreground Extraction using Iterated Graph Cuts, Rother et al. in SIGGRAPH, 2004
• Hybrid Images, Oliva et al. in SIGGRAPH, 2006
• Image Deformation Using Moving Least Squares, Schaefer et al. in SIGGRAPH, 2006
• Sketch2Photo: internet image montage, Chen et al. in SIGGRAPH Asia 2009
• Photo Clip Art, Lalonde et al. in SIGGARPH 2007
• Graphcut Textures: Image and Video Synthesis Using Graph Cuts, 2003
• ShadowDraw: Real-Time User Guidance for Freehand Drawing, 2011
• Summarizing Visual Data Using Bidirectional Similarity, 2008

Reading list:

• Deep Learning Book, Chapter 6 and 9.
• Szeliski Book, Chapter 5.3 and 5.4.
• Gradient-based learning applied to document recognition, Lecun et al., Proc of IEEE, 1998.
• Receptive Fields of Single Neurones in the Cat’s Striate Cortex, Huber and Wiesel, J. Physiol, 1959.
• Learning to Generate Chairs, Tables and Cars with Convolutional Networks, Dosovitskiy et al., PAMI 2017 (CVPR 2015)
• Deconvolution and Checkerboard Artifacts
• Colorful Image Colorization, Zhang et al., ECCV 2016.
• Deep Learning, LeCun, Bengio, and Hinton, Nature 2015.

Reading List:

• Szeliski Book, Chapter 5.5.3
• Generative Adversarial Networks, Goodfellow et al., NeurIPS 2014.
• GAN Tutorial (NeurIPS 2016), by Ian Goodfellow.
• ICCV 2017 Tutorial on GANs.
• CVPR 2018 Tutorial on GANs.
• Image style transfer using convolutional neural networks, Gatys et al., CVPR 2016.
• Perceptual Losses for Real-Time Style Transfer and Super-Resolution, Johnson et al., ECCV 2016.
• Generating images with perceptual similarity metrics based on deep networks. Dosovitskiy and Brox. NeurIPS, 2016
• The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. Zhang et al., CVPR 2018
• Image Manipulation with Perceptual Discriminators, Sungatullina et al., ECCV 2018.

Reading List:

• Szeliski Book, Chapter 5.5.3
• Generative Adversarial Networks, Goodfellow et al., NeurIPS 2014.
• GAN Tutorial (NeurIPS 2016), by Ian Goodfellow.
• ICCV 2017 Tutorial on GANs.
• CVPR 2018 Tutorial on GANs.
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks, Radford et al., ICLR 2016
• Wasserstein GAN, Arjovsky et al, 2017
• Improved Training of Wasserstein GANs, Gulrajani et al., NeurIPS 2017
• Least Squares Generative Adversarial Networks, Mao et al. 2017
• Progressive Growing of GANs for Improved Quality, Stability, and Variation, Karras et al, ICLR 2018
• Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks, Denton et al, 2015
• Spectral Normalization for Generative Adversarial Networks, Miyato et al., ICLR 2018
• A Style-Based Generator Architecture for Generative Adversarial Networks, Karras et al., CVPR 2019
• Analyzing and Improving the Image Quality of StyleGAN, Karras et al., 2020
• Alias-Free Generative Adversarial Networks, Karras et al., 2021
• Training Generative Adversarial Networks with Limited Data, Karras et al., 2020
• Differentiable Augmentation for Data-Efficient GAN Training, Zhao et al., 2020
• Projected GANs Converge Faster, Sauer et al., 2021
• Ensembling Off-the-shelf Models for GAN Training, Kumari et al., 2021

Reading List:

• Deep Learning Book, Chapter 20
• Learning Deep Generative Models, Ruslan Salakhutdinov, Annual Review of Applied Statistics 2015
• Auto-Encoding Variational Bayes, Kingma and Welling, 2013
• Density estimation using Real NVP, Dinh et al, ICLR 2017
• Conditional Image Generation with PixelCNN Decoders, Oord et al, 2016
• Pixel Recurrent Neural Networks, Oord et al, 2016
• Generating Diverse High-Fidelity Images with VQ-VAE-2, Razavi et al., 2019
• Glow: Generative flow with invertible 1x1 convolutions, Kingma et al., 2018
• Denoising Diffusion Probabilistic Models, Ho et al., 2020
• Denoising Diffusion Implicit Models, Song et al., 2021

Reading List:

• Deep Learning Book, Chapters 14 and 20
• A Style-Based Generator Architecture for Generative Adversarial Networks, Karras et al, CVPR 2019
• Large Scale GAN Training for High Fidelity Natural Image Synthesis (BigGAN), Brock et al., ICLR 2019
• Generating Diverse High-Fidelity Images with VQ-VAE-2, Razavi et al., 2019
• Conditional Image Generation with PixelCNN Decoders, Oord et al., NeurIPS 2016
• Glow: Generative Flow with Invertible 1x1 Convolutions, Kingma et al., ICLR 2018
• Analyzing and Improving the Image Quality of StyleGAN, Karras et al, 2019
• Autoencoding beyond pixels using a learned similarity metric, Larsen et al, CVPR 2016
• Denoising Diffusion Probabilistic Models, Ho et al., 2020
• Denoising Diffusion Implicit Models, Song et al., 2021
• Large scale adversarial representation learning (BigBiGAN), Donahue et al., ICLR 2019
• Alias-Free Generative Adversarial Networks (StyleGAN3), Karras et al., NeurIPS 2021
• SinGAN: Learning a Generative Model from a Single Natural Image (SinGAN), Shaham et al., ICCV 2019
• Score-Based Generative Modeling through Stochastic Differential Equations (SDE), Song et al., ICLR 2021

Reading List:

• Image-to-Image Translation with Conditional Adversarial Networks, Isola et al, CVPR 2017
• Photographic Image Synthesis with Cascaded Refinement Networks, Chen et al, ICCV 2017
• Toward Multimodal Image-to-Image Translation, Zhu et al, NeurIPS 2017
• Multi-Agent Diverse Generative Adversarial Networks, Ghosh et al, CVPR 2018
• Diversity-Sensitive Conditional Generative Adversarial Networks, Yang et al, ICLR 2019
• High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs, Wang et al, CVPR 2018.
• cGANs with Projection Discriminator, Miyato et al., ICLR 2018
• Large Scale GAN Training for High Fidelity Natural Image Synthesis, ICLR 2019
• Semantic Image Synthesis with Spatially-Adaptive Normalization, Park et al, CVPR 2019
• Shapes and Context: In-the-Wild Image Synthesis & Manipulation, Bansal et al, CVPR 2019

Reading List:

• Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks, Zhu et al, ICCV 2017
• Unsupervised Image-to-Image Translation Networks, Liu et al., NeurIPS 2017
• Learning from Simulated and Unsupervised Images through Adversarial Training, Shrivastava et al, CVPR 2017
• Unsupervised Cross-Domain Image Generation, Taigman et al, ICLR 2017
• Multimodal Unsupervised Image-to-Image Translation, Huang et al., ECCV 2018
• Representation learning with contrastive predictive coding, Oord et al., arXiv 2018.
• Contrastive learning for unpaired image-to-image translation, Park et al., ECCV 2020

Reading List:

• Separating Style and Content, Tenenbaum & Freeman, Neurips 1996
• Representation Learning with Contrastive Predictive Coding, van den Oord et al
• A Simple Framework for Contrastive Learning of Visual Representations, Chen et al, ICML 2020
• Contrastive Learning for Unpaired Image-to-Image Translation, Park et al, ECCV 2020
• Swapping Autoencoder for Deep Image Manipulation, Park et al., NeurIPS 2020.
• FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery, Singh et al., CVPR 2019.
• Texture Synthesis by Non-parametric Sampling, Efros and Leung, ICCV 1999
• Image Quilting for Texture Synthesis and Transfer, Efros and Freeman, SIGGRAPH 2001.
• Image Analogies, Hertzmann et al, SIGGRAPH 2001

Reading List:

• PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing, Barnes et al, SIGGRAPH 2009
• Visual Attribute Transfer through Deep Image Analogy, Liao et al, SIGGRAPH 2017
• Deep Photo Style Transfer, Luan et al, CVPR 2017
• Non-Stationary Texture Synthesis by Adversarial Expansion, Zhou et al, SIGGRAPH 2018
• Deep Image Harmonization, Luan et al., EGSR 2018
• Cross-domain Correspondence Learning for Exemplar-based Image Translation, Zhang et al., CVPR 2020.

Reading List:

• Semi-parametric Image Synthesis, Qi et al, CVPR 2018
• StarGAN v2: Diverse Image Synthesis for Multiple Domains, Choi et al, CVPR 2020
• FUNIT: Few-Shot Unsupervised Image-to-Image Translation, Liu et al, ICCV 2019
• The Perception-Distortion Tradeoff, Blau et al, CVPR 2018
• Style Transfer for Headshot Portraits, Shih et al, SIGGRAPH 2014
• Image Analogies, Hertzmann et al., SIGGRAPH 2001
• Controlling Perceptual Factors in Neural Style Transfer, Gatys et al., CVPR 2017
• Visual attribute transfer through deep image analogy, Liao et al, SIGGRAPH 2017
• Deep Photo Style Transfer, Luan et al., CVPR 2017
• Non-stationary Texture Synthesis by Adversarial Expansion, Zhou et al., SIGGRAPH 2018
• Cross-domain Correspondence Learning for Exemplar-based Image Translation, Zhang et al., CVPR 2020
• Sean: Image synthesis with semantic region-adaptive normalization, Zhu et al., CVPR 2020
• A closed-form solution to photorealistic image stylization, Li et al., ECCV 2018
• Multimodal Conditional Image Synthesis with Product-of-Experts GANs, Huang et al., arXiv 2021

Reading List:

• Generative Visual Manipulation on the Natural Image Manifold, Zhu et al, ECCV 2016
• Neural Photo Editing with Introspective Adversarial Networks, Brock et al, ICLR 2017
• Semantic Photo Manipulation with a Generative Image Prior, Bau et al, SIGGRAPH 2019
• Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?, Abdal et al, ICCV 2019
• StyleGAN2: Analyzing and Improving the Image Quality of StyleGAN., Karras et al, CVPR 2020
• GAN Inversion: A Survey. Xia et al. 2021

Reading List:

• GAN Dissection: Visualizing and Understanding Generative Adversarial Networks, Bau et al, ICLR 2019
• GANSpace: Discovering Interpretable GAN Controls, Härkönen et al, NeurIPS 2020
• StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation, Wu et al., CVPR 2021
• Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation, Pan et al., ECCV 2020
• On the “steerability” of generative adversarial networks, Jahanian et al, ICLR 2020
• Editing in Style: Uncovering the Local Semantics of GANs., Collins et al, CVPR 2020
• Closed-Form Factorization of Latent Semantics in GANs., Shen et al, CVPR 2021
• Pivotal Tuning for Latent-based Editing of Real Images, Roich et al., 2021

• GAN Dissection: Visualizing and Understanding Generative Adversarial Networks, Bau et al, ICLR 2019
• GANSpace: Discovering Interpretable GAN Controls, Härkönen et al, NeurIPS 2020
• Deep Image Prior, Ulyanov et al, CVPR 2018
• GANSpace: Discovering Interpretable GAN Controls, Härkönen et al, NeurIPS 2020
• Colorization using Optimization, Levin et al, SIGGRAPH 2004
• AppProp: all-pairs appearance-space edit propagation, An et al, SIGGRAPH 2008
• Image Smoothing via L0 Gradient Minimization, Xu et al, SIGGRAPH Asia 2011
• On the “steerability” of generative adversarial networks, Jahanian et al, ICLR 202
• TryOnGAN: Body-Aware Try-On via Layered Interpolation, Du et al, SIGGRAPH 2021
• StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery, Patashnik et al., ICCV 2021
• Encoding in style: a stylegan encoder for image-to-image translation, Richardson et al., CVPR 2021
• Rewriting a Deep Generative Model, Bau et al., ECCV 2020
• StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators, Gal et al., Arxiv 2021

Reading List:

• Active Appearance Models, Cootes et al, ECCV 1998
• Composite Portraits, Galton, Nature 1878
• Manipulating Facial Appearance through Shape and Color, Rowland & Perret, CG&A, 1995
• A Morphable Model For The Synthesis Of 3D Faces, Blanz & Vetter, SIGGRAPH 1999
• Eigenfaces for Recognition, Turk and Pentland, Journal of cognitive neuroscience, 1991
• Exploring Photobios, Kemelmacher-Shlizerman et al., SIGGRAPH 2011

Reading List:

• Reducing the dimensionality of data with neural networks, Hinton & Salakhutdinov, Science 2006
• Deep Video Portraits, Kim et al, SIGGRAPH 2018
• StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation, Choi et al, CVPR 2018
• StarGAN v2: Diverse Image Synthesis for Multiple Domains, Choi et al, CVPR 2020
• GANimation: Anatomically-aware Facial Animation from a Single Image, Pumarola et al, ECCV 2018
• Image2StyleGAN++: How to Edit the Embedded Images?, Abdal et al, CVPR 2020
• StyleRig: Rigging StyleGAN for 3D Control over Portrait Images, Tewari et al, CVPR 2020

Reading List:

• Face2Face: Real-time Face Capture and Reenactment of RGB Videos, Theis et al, CVPR 2016
• SfSNet: Learning Shape, Reflectance and Illuminance of Faces ‘in the wild’, Sengputa et al, CVPR 2018
• paGAN: Real-time Avatars Using Dynamic Textures, Nagano et al, SIGGRAPH Asia 2018
• Single Image Portrait Relighting, Sun et al, SIGGRAPH 2019
• Intuitive, Interactive Beard and Hair Synthesis with Generative Models, Olzewski et al., CVPR 2020
• Time Travel Rephotography, Luo et al, arXiV 2020
• One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing, Wang et al., CVPR 2021
• Lifespan Age Transformation Synthesis, Or-el et al., ECCV 2020
• StyleFlow : Attribute-conditioned Exploration of StyleGAN-generated Images using Conditional Continuous Normalizing Flows, Abdal et al., ACM TOG 2021
• Text-based Editing of Talking-head Video, Fried et al., SIGGRAPH 2019

Reading List:

• QuickTime VR – An Image-Based Approach to Virtual Environment Navigation, Chen, SIGGRAPH 1995
• Stanford Lightfield Website, 2004-2014
• View Synthesis by Appearance Flow, Zhou et al, ECCV 2016
• Single-view view synthesis with multiplane images, Tucker et al, CVPR 2020
• NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis, Mildenhall et al, ECCV 2020

Reading List:

• Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling, Wu et al, NeurIPS 2017
• Visual Object Networks: Image Generation with Disentangled 3D Representation, Zhu et al, NeurIPS 2018
• Hologan: Unsupervised learning of 3d representations from natural images, Nguyen-Phuoc et al, ICCV 2019
• DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation, Park et al, CVPR 2019
• GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis, Schwarz et al, NeurIPS 2020
• pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis, Chan et al, CVPR 2021
• Editing Conditional Radiance Fields, Liu et al, ICCV 2021
• EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks, Chan et al, arXiv 2021
• StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesis, Gu et al, arXiv 2021

Reading List:

• Interactive Video Cutout, Wang et al, SIGGRAPH 2005
• Video Object Annotation, Navigation, and Composition, Goldman et al, UIST 2008
• Recycle-GAN: Unsupervised Video Retargeting, Bansal et al, ECCV 2018
• Everybody Dance Now, Chan et al, ICCV 2019
• Adversarial Video Generation on Complex Datasets, Clark et al, arXiv 2019
• Text-based Editing of Talking-head Video, Fried at al, SIGGRAPH 2019
• Background Matting: The World is Your Green Screen, Sengupta et al, CVPR 2020
• World-Consistent Video-to-Video Synthesis, Mallya et al, ECCV 2020
• Third Time’s the Charm? Image and Video Editing with StyleGAN3, Alaluf et al, Arxiv 2021
• Learning to simulate dynamic environments with gamegan, Kim et al, CVPR 2020
• Instant Neural Graphics Primitives with a Multiresolution Hash Encoding, Muller et al, Arxiv 2022
• Light Field Photography with a Hand-held Plenoptic Camera, Ng et al, SIGGRAPH 2005
• Photo tourism: exploring photo collections in 3D, Snavely et al, SIGGRAPH 2006
• Unsupervised Learning of Depth and Ego-Motion from Video, Zhou et al, CVPR 2017
• Plenoxels, Yu et al, CVPR 2022
• Nerfies: Deformable Neural Radiance Fields, Park et al, ICCV 2021
• Unsupervised 3D Neural Rendering of Minecraft Worlds, Hao et al, ICCV 2021
• NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections, Martin-Brualla et al, CVPR 2021
• pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis, Chan et al, CVPR 2021
• EG3D: Efficient Geometry-aware 3D GANs, Chan et al, Arxiv 2021

Reading List:

• Video Textures, Sch¨odl et al., SIGGRAPH 2000
• Controlled Animation of Video Sprites, Schodl et al., UIST 2008
• Generating Videos with Scene Dynamics, Vondrick et al., NeurIPS 2016
• Video-to-Video Synthesis, Vondrick et al., NeurIPS 2016
• Recycle-GAN: Unsupervised Video Retargeting, Bansal et al, ECCV 2018
• Adversarial Video Generation on Complex Datasets, Clark et al, arXiv 2019
• Everybody Dance Now, Chan et al, ICCV 2019
• Few-shot Video-to-Video Synthesis, Wang et al., NeurIPS 2019