b'Jun-Yan Zhu'

research

∙ 03/22/2022

Dataset Distillation by Matching Training Trajectories

Dataset distillation is the task of synthesizing a small dataset such th...

George Cazenavette, et al. ∙

research

∙ 12/16/2021

Ensembling Off-the-shelf Models for GAN Training

The advent of large-scale training has produced a cornucopia of powerful...

Nupur Kumari, et al. ∙

research

∙ 12/09/2021

GAN-Supervised Dense Visual Alignment

We propose GAN-Supervised Learning, a framework for learning discriminat...

William Peebles, et al. ∙

research

∙ 11/12/2021

Contrastive Feature Loss for Image Prediction

Training supervised image synthesis models requires a critic to compare ...

Alex Andonian, et al. ∙

research

∙ 08/05/2021

Sketch Your Own GAN

Can a user create a deep generative model by sketching a single example?...

Sheng-Yu Wang, et al. ∙

research

∙ 07/06/2021

Depth-supervised NeRF: Fewer Views and Faster Training for Free

One common failure mode of Neural Radiance Field (NeRF) models is fittin...

Kangle Deng, et al. ∙

research

∙ 05/13/2021

Editing Conditional Radiance Fields

A neural radiance field (NeRF) is a scene model supporting high-quality ...

Steven Liu, et al. ∙

research

∙ 04/29/2021

Ensembling with Deep Generative Views

Recent generative models can synthesize "views" of artificial images tha...

Lucy Chai, et al. ∙

research

∙ 04/22/2021

On Buggy Resizing Libraries and Surprising Subtleties in FID Calculation

We investigate the sensitivity of the Fréchet Inception Distance (FID) s...

Gaurav Parmar, et al. ∙

research

∙ 03/04/2021

Anycost GANs for Interactive Image Synthesis and Editing

Generative adversarial networks (GANs) have enabled photorealistic image...

Ji Lin, et al. ∙

research

∙ 09/10/2020

Understanding the Role of Individual Units in a Deep Neural Network

Deep neural networks excel at finding hierarchical representations that ...

David Bau, et al. ∙

research

∙ 08/24/2020

The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement

Existing disentanglement methods for deep generative models rely on hand...

William Peebles, et al. ∙

research

∙ 07/30/2020

Contrastive Learning for Unpaired Image-to-Image Translation

In image-to-image translation, each patch in the output should reflect t...

Taesung Park, et al. ∙

research

∙ 07/30/2020

Rewriting a Deep Generative Model

A deep generative model such as a GAN learns to model a rich set of sema...

David Bau, et al. ∙

research

∙ 07/01/2020

Swapping Autoencoder for Deep Image Manipulation

Deep generative models have become increasingly effective at producing r...

Taesung Park, et al. ∙

research

∙ 06/18/2020

Differentiable Augmentation for Data-Efficient GAN Training

The performance of generative adversarial networks (GANs) heavily deteri...

Shengyu Zhao, et al. ∙

research

∙ 06/18/2020

Diverse Image Generation via Self-Conditioned GANs

We introduce a simple but effective unsupervised method for generating r...

Steven Liu, et al. ∙

research

∙ 05/15/2020

Semantic Photo Manipulation with a Generative Image Prior

Despite the recent success of GANs in synthesizing images conditioned on...

David Bau, et al. ∙

research

∙ 05/04/2020

Transforming and Projecting Images into Class-conditional Generative Networks

We present a method for projecting an input image into the space of a cl...

Minyoung Huh, et al. ∙

research

∙ 04/08/2020

State of the Art on Neural Rendering

Efficient rendering of photo-realistic virtual worlds is a long standing...

Ayush Tewari, et al. ∙

research

∙ 03/19/2020

GAN Compression: Efficient Architectures for Interactive Conditional GANs

Conditional Generative Adversarial Networks (cGANs) have enabled control...

Muyang Li, et al. ∙

research

∙ 10/24/2019

Seeing What a GAN Cannot Generate

Despite the success of Generative Adversarial Networks (GANs), mode coll...

David Bau, et al. ∙

research

∙ 06/14/2019

Connecting Touch and Vision via Cross-Modal Prediction

Humans perceive the world using multi-modal sensory inputs such as visio...

Yunzhu Li, et al. ∙

research

∙ 03/18/2019

Semantic Image Synthesis with Spatially-Adaptive Normalization

We propose spatially-adaptive normalization, a simple but effective laye...

Taesung Park, et al. ∙

research

∙ 01/29/2019

Visualizing and Understanding Generative Adversarial Networks (Extended Abstract)

Generative Adversarial Networks (GANs) have achieved impressive results ...

David Bau, et al. ∙

research

∙ 12/06/2018

Visual Object Networks: Image Generation with Disentangled 3D Representation

Recent progress in deep generative models has led to tremendous breakthr...

Jun-Yan Zhu, et al. ∙

research

∙ 11/27/2018

Dataset Distillation

Model distillation aims to distill the knowledge of a complex model into...

Tongzhou Wang, et al. ∙

research

∙ 11/26/2018

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Generative Adversarial Networks (GANs) have recently achieved impressive...

David Bau, et al. ∙

research

∙ 09/28/2018

Propagation Networks for Model-Based Control Under Partial Observation

There has been an increasing interest in learning dynamics simulators fo...

Yunzhu Li, et al. ∙

research

∙ 08/28/2018

3D-Aware Scene Manipulation via Inverse Graphics

We aim to obtain an interpretable, expressive and disentangled scene rep...

Shunyu Yao, et al. ∙

research

∙ 08/20/2018

Video-to-Video Synthesis

We study the problem of video-to-video synthesis, whose goal is to learn...

Ting-Chun Wang, et al. ∙

research

∙ 01/08/2018

Spatially transformed adversarial examples

Recent studies show that widely used deep neural networks (DNNs) are vul...

Chaowei Xiao, et al. ∙

research

∙ 01/08/2018

Generating adversarial examples with adversarial networks

Deep neural networks (DNNs) have been found to be vulnerable to adversar...

Chaowei Xiao, et al. ∙

research

∙ 11/30/2017

Toward Multimodal Image-to-Image Translation

Many image-to-image translation problems are ambiguous, as a single inpu...

Jun-Yan Zhu, et al. ∙

research

∙ 11/30/2017

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

We present a new method for synthesizing high-resolution photo-realistic...

Ting-Chun Wang, et al. ∙

research

∙ 11/08/2017

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Domain adaptation is critical for success in new, unseen environments. A...

Judy Hoffman, et al. ∙

research

∙ 05/08/2017

Real-Time User-Guided Image Colorization with Learned Deep Priors

We propose a deep learning approach for user-guided image colorization. ...

Richard Zhang, et al. ∙

research

∙ 05/08/2017

Light Field Video Capture Using a Learning-Based Hybrid Imaging System

Light field cameras have many advantages over traditional cameras, as th...

Ting-Chun Wang, et al. ∙

research

∙ 03/30/2017

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Image-to-image translation is a class of vision and graphics problems wh...

Jun-Yan Zhu, et al. ∙

research

∙ 11/21/2016

Image-to-Image Translation with Conditional Adversarial Networks

We investigate conditional adversarial networks as a general-purpose sol...

Phillip Isola, et al. ∙

research

∙ 09/12/2016

Generative Visual Manipulation on the Natural Image Manifold

Realistic image manipulation is challenging because it requires modifyin...

Jun-Yan Zhu, et al. ∙

research

∙ 08/24/2016

A 4D Light-Field Dataset and CNN Architectures for Material Recognition

We introduce a new light-field dataset of materials, and take advantage ...

Ting-Chun Wang, et al. ∙

Jun-Yan Zhu

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