Antonio Torralba

research

∙ 06/16/2022

Virtual Correspondence: Humans as a Cue for Extreme-View Geometry

Recovering the spatial layout of the cameras and the geometry of the sce...

Wei-Chiu Ma, et al. ∙

research

∙ 06/15/2022

Disentangling visual and written concepts in CLIP

The CLIP network measures the similarity between natural text and images...

Joanna Materzyńska, et al. ∙

research

∙ 06/06/2022

Polymorphic-GAN: Generating Aligned Samples across Multiple Domains with Learned Morph Maps

Modern image generative models show remarkable sample quality when train...

Seung Wook Kim, et al. ∙

research

∙ 06/03/2022

Compositional Visual Generation with Composable Diffusion Models

Large text-guided diffusion models, such as DALLE-2, are able to generat...

Nan Liu, et al. ∙

research

∙ 05/05/2022

Fixing Malfunctional Objects With Learned Physical Simulation and Functional Prediction

This paper studies the problem of fixing malfunctional 3D objects. While...

Yining Hong, et al. ∙

research

∙ 05/02/2022

ComPhy: Compositional Physical Reasoning of Objects and Events from Videos

Objects' motions in nature are governed by complex interactions and thei...

Zhenfang Chen, et al. ∙

research

∙ 04/11/2022

Correcting Robot Plans with Natural Language Feedback

When humans design cost or goal specifications for robots, they often pr...

Pratyusha Sharma, et al. ∙

research

∙ 04/04/2022

Learning Neural Acoustic Fields

Our environment is filled with rich and dynamic acoustic information. Wh...

Andrew Luo, et al. ∙

research

∙ 03/30/2022

Learning Program Representations for Food Images and Cooking Recipes

In this paper, we are interested in modeling a how-to instructional proc...

Dim P. Papadopoulos, et al. ∙

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

∙ 02/03/2022

Pre-Trained Language Models for Interactive Decision-Making

Language model (LM) pre-training has proven useful for a wide variety of...

Shuang Li, et al. ∙

research

∙ 01/26/2022

Natural Language Descriptions of Deep Visual Features

Some neurons in deep networks specialize in recognizing highly specific ...

Evan Hernandez, et al. ∙

research

∙ 01/12/2022

BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations

Annotating images with pixel-wise labels is a time-consuming and costly ...

Daiqing Li, et al. ∙

research

∙ 01/12/2022

Robust Contrastive Learning against Noisy Views

Contrastive learning relies on an assumption that positive pairs contain...

Ching-Yao Chuang, et al. ∙

research

∙ 01/11/2022

Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents

Natural disasters, such as floods, tornadoes, or wildfires, are increasi...

Ethan Weber, 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

∙ 12/09/2021

PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning

A critical aspect of human visual perception is the ability to parse vis...

Yining Hong, et al. ∙

research

∙ 12/02/2021

Editing a classifier by rewriting its prediction rules

We present a methodology for modifying the behavior of a classifier by d...

Shibani Santurkar, et al. ∙

research

∙ 11/17/2021

Learning to Compose Visual Relations

The visual world around us can be described as a structured set of objec...

Nan Liu, et al. ∙

research

∙ 11/04/2021

EditGAN: High-Precision Semantic Image Editing

Generative adversarial networks (GANs) have recently found applications ...

Huan Ling, 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...

Chuang Gan, et al. ∙

research

∙ 10/08/2021

Toward a Visual Concept Vocabulary for GAN Latent Space

A large body of recent work has identified transformations in the latent...

Sarah Schwettmann, et al. ∙

research

∙ 10/07/2021

Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions

We introduce the task of weakly supervised learning for detecting human ...

Shuang Li, et al. ∙

research

∙ 10/05/2021

Scaling up instance annotation via label propagation

Manually annotating object segmentation masks is very time-consuming. Wh...

Dim P. Papadopoulos, et al. ∙

research

∙ 10/04/2021

Skill Induction and Planning with Latent Language

We present a framework for learning hierarchical policies from demonstra...

Pratyusha Sharma, et al. ∙

research

∙ 09/09/2021

Dynamic Modeling of Hand-Object Interactions via Tactile Sensing

Tactile sensing is critical for humans to perform everyday tasks. While ...

Qiang Zhang, et al. ∙

research

∙ 08/30/2021

What You Can Learn by Staring at a Blank Wall

We present a passive non-line-of-sight method that infers the number of ...

Prafull Sharma, et al. ∙

research

∙ 07/08/2021

3D Neural Scene Representations for Visuomotor Control

Humans have a strong intuitive understanding of the 3D environment aroun...

Yunzhu Li, et al. ∙

research

∙ 06/10/2021

Learning to See by Looking at Noise

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

Manel Baradad, et al. ∙

research

∙ 06/07/2021

Measuring Generalization with Optimal Transport

Understanding the generalization of deep neural networks is one of the m...

Ching-Yao Chuang, et al. ∙

research

∙ 04/30/2021

DriveGAN: Towards a Controllable High-Quality Neural Simulation

Realistic simulators are critical for training and verifying robotics sy...

Seung Wook Kim, et al. ∙

research

∙ 04/17/2021

Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales

The past decade has witnessed a groundbreaking rise of machine learning ...

Jacob Andreas, et al. ∙

research

∙ 04/13/2021

DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort

We introduce DatasetGAN: an automatic procedure to generate massive data...

Yuxuan Zhang, et al. ∙

research

∙ 04/13/2021

BARF: Bundle-Adjusting Neural Radiance Fields

Neural Radiance Fields (NeRF) have recently gained a surge of interest w...

Chen-Hsuan Lin, et al. ∙

research

∙ 04/12/2021

Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization

Training deep networks with limited labeled data while achieving a stron...

Daiqing Li, et al. ∙

research

∙ 03/25/2021

The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI

We introduce a visually-guided and physics-driven task-and-motion planni...

Chuang Gan, et al. ∙

research

∙ 03/19/2021

Paint by Word

We investigate the problem of zero-shot semantic image painting. Instead...

David Bau, et al. ∙

research

∙ 01/19/2021

Deep Feedback Inverse Problem Solver

We present an efficient, effective, and generic approach towards solving...

Wei-Chiu Ma, et al. ∙

research

∙ 11/24/2020

Energy-Based Models for Continual Learning

We motivate Energy-Based Models (EBMs) as a promising model class for co...

Shuang Li, et al. ∙

research

∙ 10/19/2020

Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration

In this paper, we introduce Watch-And-Help (WAH), a challenge for testin...

Xavier Puig, et al. ∙

research

∙ 10/18/2020

Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering

Differentiable rendering has paved the way to training neural networks t...

Yuxuan Zhang, et al. ∙

research

∙ 10/17/2020

LID 2020: The Learning from Imperfect Data Challenge Results

Learning from imperfect data becomes an issue in many industrial applica...

Yunchao Wei, et al. ∙

research

∙ 09/14/2020

Improving Inversion and Generation Diversity in StyleGAN using a Gaussianized Latent Space

Modern Generative Adversarial Networks are capable of creating artificia...

Jonas Wulff, 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

∙ 08/20/2020

Detecting natural disasters, damage, and incidents in the wild

Responding to natural disasters, such as earthquakes, floods, and wildfi...

Ethan Weber, 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

∙ 07/27/2020

Noisy Agents: Self-supervised Exploration by Predicting Auditory Events

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

Chuang Gan, et al. ∙

research

∙ 07/21/2020

Foley Music: Learning to Generate Music from Videos

In this paper, we introduce Foley Music, a system that can synthesize pl...

Chuang Gan, et al. ∙

research

∙ 07/06/2020

Estimating Generalization under Distribution Shifts via Domain-Invariant Representations

When machine learning models are deployed on a test distribution differe...

Ching-Yao Chuang, et al. ∙

Antonio Torralba

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