Search Results for author: Greg Shakhnarovich

Found 23 papers, 12 papers with code

Open-Domain Sign Language Translation Learned from Online Video

no code implementations25 May 2022 Bowen Shi, Diane Brentari, Greg Shakhnarovich, Karen Livescu

Existing work on sign language translation--that is, translation from sign language videos into sentences in a written language--has focused mainly on (1) data collected in a controlled environment or (2) data in a specific domain, which limits the applicability to real-world settings.

Sign Language Translation Translation

Adapting CLIP For Phrase Localization Without Further Training

1 code implementation7 Apr 2022 Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh

Our method for phrase localization requires no human annotations or additional training.

Searching for fingerspelled content in American Sign Language

no code implementations ACL 2022 Bowen Shi, Diane Brentari, Greg Shakhnarovich, Karen Livescu

This is an important task since significant content in sign language is often conveyed via fingerspelling, and to our knowledge the task has not been studied before.

Natural Language Processing Translation

Neural Neighbor Style Transfer

1 code implementation24 Mar 2022 Nicholas Kolkin, Michal Kucera, Sylvain Paris, Daniel Sykora, Eli Shechtman, Greg Shakhnarovich

We propose Neural Neighbor Style Transfer (NNST), a pipeline that offers state-of-the-art quality, generalization, and competitive efficiency for artistic style transfer.

Style Transfer

Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness

no code implementations11 Feb 2022 Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang

We present an oracle-efficient algorithm for boosting the adversarial robustness of barely robust learners.

Adversarial Robustness

Self-Supervised Camera Self-Calibration from Video

no code implementations6 Dec 2021 Jiading Fang, Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon, Matthew R. Walter

Camera calibration is integral to robotics and computer vision algorithms that seek to infer geometric properties of the scene from visual input streams.

Autonomous Vehicles Camera Calibration +2

Fingerspelling Detection in American Sign Language

1 code implementation CVPR 2021 Bowen Shi, Diane Brentari, Greg Shakhnarovich, Karen Livescu

We propose a benchmark and a suite of evaluation metrics, some of which reflect the effect of detection on the downstream fingerspelling recognition task.

Pose Estimation

Full Surround Monodepth from Multiple Cameras

no code implementations31 Mar 2021 Vitor Guizilini, Igor Vasiljevic, Rares Ambrus, Greg Shakhnarovich, Adrien Gaidon

In this work, we extend monocular self-supervised depth and ego-motion estimation to large-baseline multi-camera rigs.

Autonomous Driving Motion Estimation

Information-Theoretic Segmentation by Inpainting Error Maximization

1 code implementation CVPR 2021 Pedro Savarese, Sunnie S. Y. Kim, Michael Maire, Greg Shakhnarovich, David Mcallester

We study image segmentation from an information-theoretic perspective, proposing a novel adversarial method that performs unsupervised segmentation by partitioning images into maximally independent sets.

Semantic Segmentation Unsupervised Image Segmentation

Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion

1 code implementation15 Aug 2020 Igor Vasiljevic, Vitor Guizilini, Rares Ambrus, Sudeep Pillai, Wolfram Burgard, Greg Shakhnarovich, Adrien Gaidon

Self-supervised learning has emerged as a powerful tool for depth and ego-motion estimation, leading to state-of-the-art results on benchmark datasets.

Depth Estimation Motion Estimation +2

Controlling Length in Image Captioning

1 code implementation29 May 2020 Ruotian Luo, Greg Shakhnarovich

We develop and evaluate captioning models that allow control of caption length.

Image Captioning

Space-Time-Aware Multi-Resolution Video Enhancement

1 code implementation CVPR 2020 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider the problem of space-time super-resolution (ST-SR): increasing spatial resolution of video frames and simultaneously interpolating frames to increase the frame rate.

Video Enhancement Video Super-Resolution

Detection and Description of Change in Visual Streams

no code implementations27 Mar 2020 Davis Gilton, Ruotian Luo, Rebecca Willett, Greg Shakhnarovich

This paper presents a framework for the analysis of changes in visual streams: ordered sequences of images, possibly separated by significant time gaps.

Change Detection Representation Learning

Fingerspelling recognition in the wild with iterative visual attention

2 code implementations ICCV 2019 Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Diane Brentari, Greg Shakhnarovich, Karen Livescu

In this paper we focus on recognition of fingerspelling sequences in American Sign Language (ASL) videos collected in the wild, mainly from YouTube and Deaf social media.

Hand Detection Sign Language Recognition

Deep Back-Projection Networks for Single Image Super-resolution

1 code implementation4 Apr 2019 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

Previous feed-forward architectures of recently proposed deep super-resolution networks learn the features of low-resolution inputs and the non-linear mapping from those to a high-resolution output.

Image Super-Resolution Single Image Super Resolution

American Sign Language fingerspelling recognition in the wild

no code implementations26 Oct 2018 Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane, Jonathan Michaux, Diane Brentari, Greg Shakhnarovich, Karen Livescu

As the first attempt at fingerspelling recognition in the wild, this work is intended to serve as a baseline for future work on sign language recognition in realistic conditions.

Sign Language Recognition

Task-Driven Super Resolution: Object Detection in Low-resolution Images

no code implementations30 Mar 2018 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

We consider how image super resolution (SR) can contribute to an object detection task in low-resolution images.

Image Super-Resolution object-detection +1

Deep Back-Projection Networks For Super-Resolution

18 code implementations CVPR 2018 Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita

The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output.

Image Super-Resolution Video Super-Resolution

Discriminative Metric Learning by Neighborhood Gerrymandering

no code implementations NeurIPS 2014 Shubhendu Trivedi, David Mcallester, Greg Shakhnarovich

We formulate the problem of metric learning for k nearest neighbor classification as a large margin structured prediction problem, with a latent variable representing the choice of neighbors and the task loss directly corresponding to classification error.

Classification General Classification +2

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