b'Phillip Isola'

research

∙ 06/15/2023

DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data

Current perceptual similarity metrics operate at the level of pixels and...

0 Stephanie Fu, et al. ∙

research

∙ 06/07/2023

MultiEarth 2023 – Multimodal Learning for Earth and Environment Workshop and Challenge

The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2...

0 Miriam Cha, et al. ∙

research

∙ 06/01/2023

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

We investigate the potential of learning visual representations using sy...

0 Yonglong Tian, et al. ∙

research

∙ 05/31/2023

Improving CLIP Training with Language Rewrites

Contrastive Language-Image Pre-training (CLIP) stands as one of the most...

0 Lijie Fan, et al. ∙

research

∙ 05/15/2023

Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks

This work examines the challenges of training neural networks using vect...

0 Minyoung Huh, et al. ∙

04/15/2023

How AI is Helping Change the Logistics Industry

0 Phillip Isola ∙

research

∙ 04/03/2023

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

In goal-reaching reinforcement learning (RL), the optimal value function...

0 Tongzhou Wang, et al. ∙

research

∙ 03/23/2023

Persistent Nature: A Generative Model of Unbounded 3D Worlds

Despite increasingly realistic image quality, recent 3D image generative...

0 Lucy Chai, et al. ∙

research

∙ 02/22/2023

Steerable Equivariant Representation Learning

Pre-trained deep image representations are useful for post-training task...

0 Sangnie Bhardwaj, et al. ∙

research

∙ 12/12/2022

MIRA: Mental Imagery for Robotic Affordances

Humans form mental images of 3D scenes to support counterfactual imagina...

0 Lin Yen-Chen, et al. ∙

research

∙ 11/29/2022

Procedural Image Programs for Representation Learning

Learning image representations using synthetic data allows training neur...

0 Manel Baradad, et al. ∙

research

∙ 11/28/2022

Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings

Asymmetrical distance structures (quasimetrics) are ubiquitous in our li...

0 Tongzhou Wang, et al. ∙

research

∙ 11/23/2022

Powderworld: A Platform for Understanding Generalization via Rich Task Distributions

One of the grand challenges of reinforcement learning is the ability to ...

0 Kevin Frans, et al. ∙

research

∙ 09/26/2022

Totems: Physical Objects for Verifying Visual Integrity

We introduce a new approach to image forensics: placing physical refract...

4 Jingwei Ma, et al. ∙

research

∙ 07/14/2022

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government ...

5 Vijay Gadepally, et al. ∙

research

∙ 06/30/2022

On the Learning and Learnablity of Quasimetrics

Our world is full of asymmetries. Gravity and wind can make reaching a p...

0 Tongzhou Wang, et al. ∙

research

∙ 06/30/2022

Denoised MDPs: Learning World Models Better Than the World Itself

The ability to separate signal from noise, and reason with clean abstrac...

8 Tongzhou Wang, et al. ∙

research

∙ 04/15/2022

MultiEarth 2022 – Multimodal Learning for Earth and Environment Workshop and Challenge

The Multimodal Learning for Earth and Environment Challenge (MultiEarth ...

0 Miriam Cha, et al. ∙

research

∙ 04/14/2022

Any-resolution Training for High-resolution Image Synthesis

Generative models operate at fixed resolution, even though natural image...

4 Lucy Chai, et al. ∙

research

∙ 03/31/2022

Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models

Prompting has recently become a popular paradigm for adapting language m...

3 Hyojin Bahng, et al. ∙

research

∙ 03/23/2022

Learning to generate line drawings that convey geometry and semantics

This paper presents an unpaired method for creating line drawings from p...

0 Caroline Chan, et al. ∙

research

∙ 03/03/2022

NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields

Thin, reflective objects such as forks and whisks are common in our dail...

8 Lin Yen-Chen, et al. ∙

research

∙ 11/12/2021

Contrastive Feature Loss for Image Prediction

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

0 Alex Andonian, et al. ∙

research

∙ 10/28/2021

Learning to Ground Multi-Agent Communication with Autoencoders

Communication requires having a common language, a lingua franca, betwee...

0 Toru Lin, et al. ∙

research

∙ 10/14/2021

The Neural MMO Platform for Massively Multiagent Research

Neural MMO is a computationally accessible research platform that combin...

0 Joseph Suarez, et al. ∙

research

∙ 10/13/2021

OPEn: An Open-ended Physics Environment for Learning Without a Task

Humans have mental models that allow them to plan, experiment, and reaso...

57 Chuang Gan, et al. ∙

research

∙ 07/15/2021

Adaptable Agent Populations via a Generative Model of Policies

In the natural world, life has found innumerable ways to survive and oft...

0 Kenneth Derek, et al. ∙

research

∙ 07/01/2021

Learning to See before Learning to Act: Visual Pre-training for Manipulation

Does having visual priors (e.g. the ability to detect objects) facilitat...

4 Lin Yen-Chen, et al. ∙

research

∙ 06/10/2021

Learning to See by Looking at Noise

Current vision systems are trained on huge datasets, and these datasets ...

0 Manel Baradad, et al. ∙

research

∙ 06/09/2021

Generative Models as a Data Source for Multiview Representation Learning

Generative models are now capable of producing highly realistic images t...

15 Ali Jahanian, et al. ∙

research

∙ 05/03/2021

Curious Representation Learning for Embodied Intelligence

Self-supervised representation learning has achieved remarkable success ...

0 Yilun Du, et al. ∙

research

∙ 04/29/2021

Ensembling with Deep Generative Views

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

7 Lucy Chai, et al. ∙

research

∙ 04/27/2021

Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Image classification models can depend on multiple different semantic at...

12 Oran Lang, et al. ∙

research

∙ 03/18/2021

The Low-Rank Simplicity Bias in Deep Networks

Modern deep neural networks are highly over-parameterized compared to th...

0 Minyoung Huh, et al. ∙

research

∙ 03/18/2021

Using latent space regression to analyze and leverage compositionality in GANs

In recent years, Generative Adversarial Networks have become ubiquitous ...

6 Lucy Chai, et al. ∙

research

∙ 12/10/2020

iNeRF: Inverting Neural Radiance Fields for Pose Estimation

We present iNeRF, a framework that performs pose estimation by "invertin...

0 Lin Yen-Chen, et al. ∙

research

∙ 08/24/2020

What makes fake images detectable? Understanding properties that generalize

The quality of image generation and manipulation is reaching impressive ...

41 Lucy Chai, et al. ∙

research

∙ 07/27/2020

Noisy Agents: Self-supervised Exploration by Predicting Auditory Events

Humans integrate multiple sensory modalities (e.g. visual and audio) to ...

1 Chuang Gan, et al. ∙

research

∙ 05/20/2020

What makes for good views for contrastive learning

Contrastive learning between multiple views of the data has recently ach...

16 Yonglong Tian, et al. ∙

research

∙ 05/20/2020

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere

Contrastive representation learning has been outstandingly successful in...

12 Tongzhou Wang, et al. ∙

research

∙ 03/25/2020

Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?

The focus of recent meta-learning research has been on the development o...

27 Yonglong Tian, et al. ∙

research

∙ 01/31/2020

Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks

Progress in multiagent intelligence research is fundamentally limited by...

7 Joseph Suarez, et al. ∙

research

∙ 11/12/2019

Experience-Embedded Visual Foresight

Visual foresight gives an agent a window into the future, which it can u...

9 Lin Yen-Chen, et al. ∙

research

∙ 10/23/2019

Contrastive Representation Distillation

Often we wish to transfer representational knowledge from one neural net...

12 Yonglong Tian, et al. ∙

research

∙ 10/01/2019

Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video

Pushing is a fundamental robotic skill. Existing work has shown how to e...

7 Maria Bauza, et al. ∙

research

∙ 07/16/2019

On the "steerability" of generative adversarial networks

An open secret in contemporary machine learning is that many models work...

5 Ali Jahanian, et al. ∙

research

∙ 06/24/2019

GANalyze: Toward Visual Definitions of Cognitive Image Properties

We introduce a framework that uses Generative Adversarial Networks (GANs...

9 Authors, et al. ∙

research

∙ 06/13/2019

Contrastive Multiview Coding

Humans view the world through many sensory channels, e.g., the long-wave...

1 Yonglong Tian, et al. ∙

research

∙ 03/02/2019

Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents

The emergence of complex life on Earth is often attributed to the arms r...

6 Joseph Suarez, et al. ∙

research

∙ 02/14/2019

Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity

Contemporary sensorimotor learning approaches typically start with an ex...

12 Deepak Pathak, et al. ∙

Phillip Isola

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