Bharath Hariharan

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Facebook ∙ cornell university ∙ berkeley college

Assistant Professor of Computer Science at Cornell University, postdoc working with Ross Girshick, Piotr Dollár, Larry Zitnick, Laurens van der Maaten and other amazing people at Facebook AI Research, PhD at beautiful Berkeley.

Self-training for Few-shot Transfer Across Extreme Task Differences

All few-shot learning techniques must be pre-trained on a large, labeled...
10/15/2020 ∙ by Cheng Perng Phoo, et al. ∙ 0 ∙ share

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Learning Gradient Fields for Shape Generation

In this work, we propose a novel technique to generate shapes from point...
08/14/2020 ∙ by Ruojin Cai, et al. ∙ 25 ∙ share

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Wasserstein Distances for Stereo Disparity Estimation

Existing approaches to depth or disparity estimation output a distributi...
07/06/2020 ∙ by Divyansh Garg, et al. ∙ 0 ∙ share

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Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

In the domain of autonomous driving, deep learning has substantially imp...
05/17/2020 ∙ by Yan Wang, et al. ∙ 18 ∙ share

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Learning Feature Descriptors using Camera Pose Supervision

Recent research on learned visual descriptors has shown promising improv...
04/28/2020 ∙ by Qianqian Wang, et al. ∙ 2 ∙ share

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Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset

In this work we explore the task of instance segmentation with attribute...
04/26/2020 ∙ by Menglin Jia, et al. ∙ 2 ∙ share

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Extending and Analyzing Self-Supervised Learning Across Domains

Self-supervised representation learning has achieved impressive results ...
04/24/2020 ∙ by Bram Wallace, et al. ∙ 0 ∙ share

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End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection

Reliable and accurate 3D object detection is a necessity for safe autono...
04/07/2020 ∙ by Rui Qian, et al. ∙ 6 ∙ share

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Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition

Few-shot, fine-grained classification requires a model to learn subtle, ...
04/01/2020 ∙ by Luming Tang, et al. ∙ 8 ∙ share

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LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images

Object segmentation in three-dimensional (3-D) point clouds is a critica...
10/30/2019 ∙ by Brian H. Wang, et al. ∙ 11 ∙ share

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When Does Self-supervision Improve Few-shot Learning?

We present a technique to improve the generalization of deep representat...
10/08/2019 ∙ by Jong-Chyi Su, et al. ∙ 19 ∙ share

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On the Efficacy of Knowledge Distillation

In this paper, we present a thorough evaluation of the efficacy of knowl...
10/03/2019 ∙ by Jang Hyun Cho, et al. ∙ 0 ∙ share

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Few-Shot Generalization for Single-Image 3D Reconstruction via Priors

Recent work on single-view 3D reconstruction shows impressive results, b...
09/03/2019 ∙ by Bram Wallace, et al. ∙ 0 ∙ share

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GeoStyle: Discovering Fashion Trends and Events

Understanding fashion styles and trends is of great potential interest t...
08/29/2019 ∙ by Utkarsh Mall, et al. ∙ 7 ∙ share

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PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

As 3D point clouds become the representation of choice for multiple visi...
06/28/2019 ∙ by Guandao Yang, et al. ∙ 5 ∙ share

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Boosting Supervision with Self-Supervision for Few-shot Learning

We present a technique to improve the transferability of deep representa...
06/17/2019 ∙ by Jong-Chyi Su, et al. ∙ 6 ∙ share

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Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving

Detecting objects such as cars and pedestrians in 3D plays an indispensa...
06/14/2019 ∙ by Yurong You, et al. ∙ 20 ∙ share

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Few-Shot Learning with Localization in Realistic Settings

Traditional recognition methods typically require large, artificially-ba...
04/09/2019 ∙ by Davis Wertheimer, et al. ∙ 0 ∙ share

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Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

3D object detection is an essential task in autonomous driving. Recent t...
12/18/2018 ∙ by Yan Wang, et al. ∙ 16 ∙ share

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A Deep-Learning-Based Fashion Attributes Detection Model

Analyzing fashion attributes is essential in the fashion design process....
10/24/2018 ∙ by Menglin Jia, et al. ∙ 0 ∙ share

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Deep Fundamental Matrix Estimation without Correspondences

Estimating fundamental matrices is a classic problem in computer vision....
10/03/2018 ∙ by Omid Poursaeed, et al. ∙ 1 ∙ share

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Resource Aware Person Re-identification across Multiple Resolutions

Not all people are equally easy to identify: color statistics might be e...
05/22/2018 ∙ by Yan Wang, et al. ∙ 0 ∙ share

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Low-Shot Learning from Imaginary Data

Humans can quickly learn new visual concepts, perhaps because they can e...
01/16/2018 ∙ by Yu-Xiong Wang, et al. ∙ 0 ∙ share

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Low-shot learning with large-scale diffusion

This paper considers the problem of inferring image labels for which onl...
06/07/2017 ∙ by Matthijs Douze, et al. ∙ 0 ∙ share

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Inferring and Executing Programs for Visual Reasoning

Existing methods for visual reasoning attempt to directly map inputs to ...
05/10/2017 ∙ by Justin Johnson, et al. ∙ 0 ∙ share

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CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

When building artificial intelligence systems that can reason and answer...
12/20/2016 ∙ by Justin Johnson, et al. ∙ 0 ∙ share

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Learning Features by Watching Objects Move

This paper presents a novel yet intuitive approach to unsupervised featu...
12/19/2016 ∙ by Deepak Pathak, et al. ∙ 0 ∙ share

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Feature Pyramid Networks for Object Detection

Feature pyramids are a basic component in recognition systems for detect...
12/09/2016 ∙ by Tsung-Yi Lin, et al. ∙ 0 ∙ share

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Low-shot Visual Recognition by Shrinking and Hallucinating Features

Low-shot visual learning---the ability to recognize novel object categor...
06/09/2016 ∙ by Bharath Hariharan, et al. ∙ 0 ∙ share

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Iterative Instance Segmentation

Existing methods for pixel-wise labelling tasks generally disregard the ...
11/26/2015 ∙ by Ke Li, et al. ∙ 0 ∙ share

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DeepBox: Learning Objectness with Convolutional Networks

Existing object proposal approaches use primarily bottom-up cues to rank...
05/08/2015 ∙ by Weicheng Kuo, et al. ∙ 0 ∙ share

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Hypercolumns for Object Segmentation and Fine-grained Localization

Recognition algorithms based on convolutional networks (CNNs) typically ...
11/21/2014 ∙ by Bharath Hariharan, et al. ∙ 0 ∙ share

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Simultaneous Detection and Segmentation

We aim to detect all instances of a category in an image and, for each i...
07/07/2014 ∙ by Bharath Hariharan, et al. ∙ 0 ∙ share

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R-CNNs for Pose Estimation and Action Detection

We present convolutional neural networks for the tasks of keypoint (pose...
06/19/2014 ∙ by Georgia Gkioxari, et al. ∙ 0 ∙ share

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Bharath Hariharan

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