b'Abhinav Gupta'

research

∙ 12/06/2019

ClusterFit: Improving Generalization of Visual Representations

Pre-training convolutional neural networks with weakly-supervised and se...

0 Xueting Yan, et al. ∙

research

∙ 11/21/2019

Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller

We study a generalized setup for learning from demonstration to build an...

0 Pratyusha Sharma, et al. ∙

research

∙ 10/08/2019

Object-centric Forward Modeling for Model Predictive Control

We present an approach to learn an object-centric forward model, and sho...

7 Yufei Ye, et al. ∙

research

∙ 09/30/2019

Efficient Bimanual Manipulation Using Learned Task Schemas

We address the problem of effectively composing skills to solve sparse-r...

0 Rohan Chitnis, et al. ∙

research

∙ 08/25/2019

Dynamics-aware Embeddings

In this paper we consider self-supervised representation learning to imp...

5 William Whitney, et al. ∙

research

∙ 08/22/2019

Compositional Video Prediction

We present an approach for pixel-level future prediction given an input ...

3 Yufei Ye, et al. ∙

research

∙ 07/26/2019

Environment Probing Interaction Policies

A key challenge in reinforcement learning (RL) is environment generaliza...

0 Wenxuan Zhou, et al. ∙

research

∙ 07/23/2019

Canonical Surface Mapping via Geometric Cycle Consistency

We explore the task of Canonical Surface Mapping (CSM). Specifically, gi...

9 Nilesh Kulkarni, et al. ∙

research

∙ 06/19/2019

PyRobot: An Open-source Robotics Framework for Research and Benchmarking

This paper introduces PyRobot, an open-source robotics framework for res...

9 Adithyavairavan Murali, et al. ∙

research

∙ 06/10/2019

Self-Supervised Exploration via Disagreement

Efficient exploration is a long-standing problem in sensorimotor learnin...

0 Deepak Pathak, et al. ∙

research

∙ 06/06/2019

3D-RelNet: Joint Object and Relational Network for 3D Prediction

We propose an approach to predict the 3D shape and pose for the objects ...

0 Nilesh Kulkarni, et al. ∙

research

∙ 05/15/2019

Task-Driven Modular Networks for Zero-Shot Compositional Learning

One of the hallmarks of human intelligence is the ability to compose lea...

0 Senthil Purushwalkam, et al. ∙

research

∙ 05/03/2019

Scaling and Benchmarking Self-Supervised Visual Representation Learning

Self-supervised learning aims to learn representations from the data its...

0 Priya Goyal, et al. ∙

research

∙ 04/15/2019

Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces

We introduce an approach to model surface properties governing bounces i...

0 Senthil Purushwalkam, et al. ∙

research

∙ 03/05/2019

Learning Exploration Policies for Navigation

Numerous past works have tackled the problem of task-driven navigation. ...

0 Tao Chen, et al. ∙

research

∙ 11/24/2018

Hardware Conditioned Policies for Multi-Robot Transfer Learning

Deep reinforcement learning could be used to learn dexterous robotic pol...

0 Tao Chen, et al. ∙

research

∙ 10/16/2018

Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation

In recent years, we have seen an emergence of data-driven approaches in ...

0 Pratyusha Sharma, et al. ∙

research

∙ 10/15/2018

Visual Semantic Navigation using Scene Priors

How do humans navigate to target objects in novel scenes? Do we use the ...

0 Wei Yang, et al. ∙

research

∙ 09/05/2018

BOLD5000: A public fMRI dataset of 5000 images

Vision science, particularly machine vision, has been revolutionized by ...

2 Nadine Chang, et al. ∙

research

∙ 08/29/2018

Interpretable Intuitive Physics Model

Humans have a remarkable ability to use physical commonsense and predict...

0 Tian Ye, et al. ∙

research

∙ 07/18/2018

Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias

Data-driven approaches to solving robotic tasks have gained a lot of tra...

10 Abhinav Gupta, et al. ∙

research

∙ 06/05/2018

Videos as Space-Time Region Graphs

How do humans recognize the action "opening a book" ? We argue that ther...

2 Xiaolong Wang, et al. ∙

research

∙ 05/10/2018

Learning to Grasp Without Seeing

Can a robot grasp an unknown object without seeing it? In this paper, we...

0 Adithyavairavan Murali, et al. ∙

research

∙ 04/25/2018

Actor and Observer: Joint Modeling of First and Third-Person Videos

Several theories in cognitive neuroscience suggest that when people inte...

2 Gunnar A. Sigurdsson, et al. ∙

research

∙ 04/25/2018

Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos

In Actor and Observer we introduced a dataset linking the first and thir...

0 Gunnar A. Sigurdsson, et al. ∙

research

∙ 04/09/2018

Binge Watching: Scaling Affordance Learning from Sitcoms

In recent years, there has been a renewed interest in jointly modeling p...

2 Xiaolong Wang, et al. ∙

research

∙ 03/29/2018

Iterative Visual Reasoning Beyond Convolutions

We present a novel framework for iterative visual reasoning. Our framewo...

0 Xinlei Chen, et al. ∙

research

∙ 03/21/2018

Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs

We consider the problem of zero-shot recognition: learning a visual clas...

0 Xiaolong Wang, et al. ∙

research

∙ 12/14/2017

AI2-THOR: An Interactive 3D Environment for Visual AI

We introduce The House Of inteRactions (THOR), a framework for visual AI...

0 Eric Kolve, et al. ∙

research

∙ 12/04/2017

Learning by Asking Questions

We introduce an interactive learning framework for the development and t...

0 Ishan Misra, et al. ∙

research

∙ 11/21/2017

Non-local Neural Networks

Both convolutional and recurrent operations are building blocks that pro...

0 Xiaolong Wang, et al. ∙

research

∙ 08/24/2017

Learning 6-DOF Grasping Interaction with Deep Geometry-aware 3D Representations

This paper focuses on the problem of learning 6-DOF grasping with a para...

0 Xinchen Yan, et al. ∙

research

∙ 08/09/2017

Transitive Invariance for Self-supervised Visual Representation Learning

Learning visual representations with self-supervised learning has become...

0 Xiaolong Wang, et al. ∙

research

∙ 08/09/2017

What Actions are Needed for Understanding Human Actions in Videos?

What is the right way to reason about human activities? What directions ...

0 Gunnar A. Sigurdsson, et al. ∙

research

∙ 08/04/2017

CASSL: Curriculum Accelerated Self-Supervised Learning

Recent self-supervised learning approaches focus on using a few thousand...

0 Adithyavairavan Murali, et al. ∙

research

∙ 08/02/2017

Combining Keystroke Dynamics and Face Recognition for User Verification

The massive explosion and ubiquity of computing devices and the outreach...

0 Abhinav Gupta, et al. ∙

research

∙ 08/02/2017

Temporal Dynamic Graph LSTM for Action-driven Video Object Detection

In this paper, we investigate a weakly-supervised object detection frame...

0 Yuan Yuan, et al. ∙

research

∙ 07/10/2017

Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

The success of deep learning in vision can be attributed to: (a) models ...

0 Chen Sun, et al. ∙

research

∙ 05/23/2017

Visual Semantic Planning using Deep Successor Representations

A crucial capability of real-world intelligent agents is their ability t...

0 Yuke Zhu, et al. ∙

research

∙ 05/16/2017

WebVision Challenge: Visual Learning and Understanding With Web Data

We present the 2017 WebVision Challenge, a public image recognition chal...

0 Wen Li, et al. ∙

research

∙ 04/12/2017

What's in a Question: Using Visual Questions as a Form of Supervision

Collecting fully annotated image datasets is challenging and expensive. ...

0 Siddha Ganju, et al. ∙

research

∙ 04/11/2017

A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

How do we learn an object detector that is invariant to occlusions and d...

0 Xiaolong Wang, et al. ∙

research

∙ 04/10/2017

ActionVLAD: Learning spatio-temporal aggregation for action classification

In this work, we introduce a new video representation for action classif...

0 Rohit Girdhar, et al. ∙

research

∙ 03/08/2017

Robust Adversarial Reinforcement Learning

Deep neural networks coupled with fast simulation and improved computati...

0 Lerrel Pinto, et al. ∙

research

∙ 02/21/2017

PixelNet: Representation of the pixels, by the pixels, and for the pixels

We explore design principles for general pixel-level prediction problems...

0 Aayush Bansal, et al. ∙

research

∙ 02/07/2017

An Implementation of Faster RCNN with Study for Region Sampling

We adapted the join-training scheme of Faster RCNN framework from Caffe ...

0 Xinlei Chen, et al. ∙

research

∙ 01/06/2017

Learning From Noisy Large-Scale Datasets With Minimal Supervision

We present an approach to effectively use millions of images with noisy ...

0 Andreas Veit, et al. ∙

research

∙ 12/20/2016

Beyond Skip Connections: Top-Down Modulation for Object Detection

In recent years, we have seen tremendous progress in the field of object...

0 Abhinav Shrivastava, et al. ∙

research

∙ 12/20/2016

From Images to 3D Shape Attributes

Our goal in this paper is to investigate properties of 3D shape that can...

0 David F. Fouhey, et al. ∙

research

∙ 12/19/2016

Asynchronous Temporal Fields for Action Recognition

Actions are more than just movements and trajectories: we cook to eat an...

0 Gunnar A. Sigurdsson, et al. ∙

Abhinav Gupta

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