Search Results for author: Saurabh Gupta

Found 48 papers, 14 papers with code

Contextual Rephrase Detection for Reducing Friction in Dialogue Systems

no code implementations EMNLP 2021 Zhuoyi Wang, Saurabh Gupta, Jie Hao, Xing Fan, Dingcheng Li, Alexander Hanbo Li, Chenlei Guo

Rephrase detection is used to identify the rephrases and has long been treated as a task with pairwise input, which does not fully utilize the contextual information (e. g. users’ implicit feedback).


Predicting Motion Plans for Articulating Everyday Objects

no code implementations2 Mar 2023 Arjun Gupta, Max E. Shepherd, Saurabh Gupta

Our key insight is to cast it as a learning problem to leverage past experience of solving similar planning problems to directly predict motion plans for mobile manipulation tasks in novel situations at test time.

Motion Planning motion prediction

One-shot Visual Imitation via Attributed Waypoints and Demonstration Augmentation

no code implementations9 Feb 2023 Matthew Chang, Saurabh Gupta

In this paper, we analyze the behavior of existing techniques and design new solutions for the problem of one-shot visual imitation.

Data Augmentation

TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors

no code implementations21 Jul 2022 Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley, Paul Schydlo, Michael J. Tarr, Saurabh Gupta, Katerina Fragkiadaki

We introduce TIDEE, an embodied agent that tidies up a disordered scene based on learned commonsense object placement and room arrangement priors.

Learning Value Functions from Undirected State-only Experience

no code implementations ICLR 2022 Matthew Chang, Arjun Gupta, Saurabh Gupta

We show that LAQ can recover value functions that have high correlation with value functions learned using ground truth actions.

Future prediction Imitation Learning +3

Detection of Distracted Driver using Convolution Neural Network

no code implementations7 Apr 2022 Narayana Darapaneni, Jai Arora, MoniShankar Hazra, Naman Vig, Simrandeep Singh Gandhi, Saurabh Gupta, Anwesh Reddy Paduri

With over 50 million car sales annually and over 1. 3 million deaths every year due to motor accidents we have chosen this space.

imdpGAN: Generating Private and Specific Data with Generative Adversarial Networks

no code implementations29 Sep 2020 Saurabh Gupta, Arun Balaji Buduru, Ponnurangam Kumaraguru

With experiments on MNIST dataset, we show that imdpGAN preserves the privacy of the individual data point, and learns latent codes to control the specificity of the generated samples.


Multi-objective Reinforcement Learning based approach for User-Centric Power Optimization in Smart Home Environments

no code implementations29 Sep 2020 Saurabh Gupta, Siddhant Bhambri, Karan Dhingra, Arun Balaji Buduru, Ponnurangam Kumaraguru

We experiment on real-world smart home data, and show that the multi-objective approaches: i) establish trade-off between the two objectives, ii) achieve better combined user satisfaction and power consumption than single-objective approaches.

Management Multi-Objective Reinforcement Learning

Aligning Videos in Space and Time

no code implementations ECCV 2020 Senthil Purushwalkam, Tian Ye, Saurabh Gupta, Abhinav Gupta

During training, given a pair of videos, we compute cycles that connect patches in a given frame in the first video by matching through frames in the second video.

Semantic Visual Navigation by Watching YouTube Videos

1 code implementation NeurIPS 2020 Matthew Chang, Arjun Gupta, Saurabh Gupta

Semantic cues and statistical regularities in real-world environment layouts can improve efficiency for navigation in novel environments.

Q-Learning Visual Navigation

Semantic Curiosity for Active Visual Learning

no code implementations ECCV 2020 Devendra Singh Chaplot, Helen Jiang, Saurabh Gupta, Abhinav Gupta

Instead, we explore a self-supervised approach for training our exploration policy by introducing a notion of semantic curiosity.

object-detection Object Detection

Neural Topological SLAM for Visual Navigation

no code implementations CVPR 2020 Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta

This paper studies the problem of image-goal navigation which involves navigating to the location indicated by a goal image in a novel previously unseen environment.

Visual Navigation

Learning to Explore using Active Neural SLAM

2 code implementations ICLR 2020 Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov

The use of learning provides flexibility with respect to input modalities (in the SLAM module), leverages structural regularities of the world (in global policies), and provides robustness to errors in state estimation (in local policies).

PointGoal Navigation

Use the Force, Luke! Learning to Predict Physical Forces by Simulating Effects

1 code implementation CVPR 2020 Kiana Ehsani, Shubham Tulsiani, Saurabh Gupta, Ali Farhadi, Abhinav Gupta

Our quantitative and qualitative results show that (a) we can predict meaningful forces from videos whose effects lead to accurate imitation of the motions observed, (b) by jointly optimizing for contact point and force prediction, we can improve the performance on both tasks in comparison to independent training, and (c) we can learn a representation from this model that generalizes to novel objects using few shot examples.

Human-Object Interaction Detection

Intrinsic Motivation for Encouraging Synergistic Behavior

no code implementations ICLR 2020 Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, Abhinav Gupta

Our key idea is that a good guiding principle for intrinsic motivation in synergistic tasks is to take actions which affect the world in ways that would not be achieved if the agents were acting on their own.

Learning to Move with Affordance Maps

1 code implementation ICLR 2020 William Qi, Ravi Teja Mullapudi, Saurabh Gupta, Deva Ramanan

In this paper, we combine the best of both worlds with a modular approach that learns a spatial representation of a scene that is trained to be effective when coupled with traditional geometric planners.

Autonomous Navigation Navigate +1

Making Smart Homes Smarter: Optimizing Energy Consumption with Human in the Loop

no code implementations6 Dec 2019 Mudit Verma, Siddhant Bhambri, Saurabh Gupta, Arun Balaji Buduru

Rapid advancements in the Internet of Things (IoT) have facilitated more efficient deployment of smart environment solutions for specific user requirement.

Reinforcement Learning (RL)

FineText: Text Classification via Attention-based Language Model Fine-tuning

no code implementations25 Oct 2019 Yunzhe Tao, Saurabh Gupta, Satyapriya Krishna, Xiong Zhou, Orchid Majumder, Vineet Khare

Training deep neural networks from scratch on natural language processing (NLP) tasks requires significant amount of manually labeled text corpus and substantial time to converge, which usually cannot be satisfied by the customers.

Benchmarking General Classification +4

Efficient Bimanual Manipulation Using Learned Task Schemas

no code implementations30 Sep 2019 Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, Abhinav Gupta

Our insight is that for many tasks, the learning process can be decomposed into learning a state-independent task schema (a sequence of skills to execute) and a policy to choose the parameterizations of the skills in a state-dependent manner.

Hashtags are (not) judgemental: The untold story of Lok Sabha elections 2019

no code implementations16 Sep 2019 Saurabh Gupta, Asmit Kumar Singh, Arun Balaji Buduru, Ponnurangam Kumaraguru

In the political context, hashtags on Twitter are used by users to campaign for their parties, spread news, or to get followers and get a general idea by following a discussion built around a hashtag.

Semantic Similarity Semantic Textual Similarity

Learning Navigation Subroutines from Egocentric Videos

no code implementations29 May 2019 Ashish Kumar, Saurabh Gupta, Jitendra Malik

We demonstrate our proposed approach in context of navigation, and show that we can successfully learn consistent and diverse visuomotor subroutines from passive egocentric videos.

Pseudo Label

Combining Optimal Control and Learning for Visual Navigation in Novel Environments

no code implementations6 Mar 2019 Somil Bansal, Varun Tolani, Saurabh Gupta, Jitendra Malik, Claire Tomlin

Model-based control is a popular paradigm for robot navigation because it can leverage a known dynamics model to efficiently plan robust robot trajectories.

Robot Navigation Visual Navigation

Visual Memory for Robust Path Following

no code implementations NeurIPS 2018 Ashish Kumar, Saurabh Gupta, David Fouhey, Sergey Levine, Jitendra Malik

Equipped with this abstraction, a second network observes the world and decides how to act to retrace the path under noisy actuation and a changing environment.

Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

2 code implementations16 Sep 2018 Michael Danielczuk, Matthew Matl, Saurabh Gupta, Andrew Li, Andrew Lee, Jeffrey Mahler, Ken Goldberg

We train a variant of Mask R-CNN with domain randomization on the generated dataset to perform category-agnostic instance segmentation without any hand-labeled data and we evaluate the trained network, which we refer to as Synthetic Depth (SD) Mask R-CNN, on a set of real, high-resolution depth images of challenging, densely-cluttered bins containing objects with highly-varied geometry.

Object Tracking Semantic Segmentation +1

Unifying Map and Landmark Based Representations for Visual Navigation

no code implementations21 Dec 2017 Saurabh Gupta, David Fouhey, Sergey Levine, Jitendra Malik

This works presents a formulation for visual navigation that unifies map based spatial reasoning and path planning, with landmark based robust plan execution in noisy environments.

Navigate Visual Navigation

Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene

no code implementations CVPR 2018 Shubham Tulsiani, Saurabh Gupta, David Fouhey, Alexei A. Efros, Jitendra Malik

The goal of this paper is to take a single 2D image of a scene and recover the 3D structure in terms of a small set of factors: a layout representing the enclosing surfaces as well as a set of objects represented in terms of shape and pose.

Learning With Side Information Through Modality Hallucination

no code implementations CVPR 2016 Judy Hoffman, Saurabh Gupta, Trevor Darrell

Thus, our method transfers information commonly extracted from depth training data to a network which can extract that information from the RGB counterpart.

object-detection Object Detection

Cross Modal Distillation for Supervision Transfer

1 code implementation CVPR 2016 Saurabh Gupta, Judy Hoffman, Jitendra Malik

In this work we propose a technique that transfers supervision between images from different modalities.

Optical Flow Estimation

Aligning 3D Models to RGB-D Images of Cluttered Scenes

no code implementations CVPR 2015 Saurabh Gupta, Pablo Arbelaez, Ross Girshick, Jitendra Malik

The goal of this work is to represent objects in an RGB-D scene with corresponding 3D models from a library.

Visual Semantic Role Labeling

1 code implementation17 May 2015 Saurabh Gupta, Jitendra Malik

In this paper we introduce the problem of Visual Semantic Role Labeling: given an image we want to detect people doing actions and localize the objects of interaction.

Action Classification Action Recognition +2

Inferring 3D Object Pose in RGB-D Images

no code implementations16 Feb 2015 Saurabh Gupta, Pablo Arbeláez, Ross Girshick, Jitendra Malik

The goal of this work is to replace objects in an RGB-D scene with corresponding 3D models from a library.

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