Search Results for author: Boyi Li

Found 12 papers, 8 papers with code

Single Image Texture Translation for Data Augmentation

1 code implementation25 Jun 2021 Boyi Li, Yin Cui, Tsung-Yi Lin, Serge Belongie

In this paper, we explore the use of Single Image Texture Translation (SITT) for data augmentation.

Data Augmentation Few-Shot Image Classification +2

WiCV 2020: The Seventh Women In Computer Vision Workshop

no code implementations11 Jan 2021 Hazel Doughty, Nour Karessli, Kathryn Leonard, Boyi Li, Carianne Martinez, Azadeh Mobasher, Arsha Nagrani, Srishti Yadav

It provides a voice to a minority (female) group in computer vision community and focuses on increasingly the visibility of these researchers, both in academia and industry.

On Feature Normalization and Data Augmentation

1 code implementation CVPR 2021 Boyi Li, Felix Wu, Ser-Nam Lim, Serge Belongie, Kilian Q. Weinberger

The moments (a. k. a., mean and standard deviation) of latent features are often removed as noise when training image recognition models, to increase stability and reduce training time.

Data Augmentation Domain Generalization +2

Integrated Triaging for Fast Reading Comprehension

no code implementations28 Sep 2019 Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger

This paper introduces Integrated Triaging, a framework that prunes almost all context in early layers of a network, leaving the remaining (deep) layers to scan only a tiny fraction of the full corpus.

Machine Reading Comprehension

Neural Network Out-of-Distribution Detection for Regression Tasks

no code implementations25 Sep 2019 Geoff Pleiss, Amauri Souza, Joseph Kim, Boyi Li, Kilian Q. Weinberger

Neural network out-of-distribution (OOD) detection aims to identify when a model is unable to generalize to new inputs, either due to covariate shift or anomalous data.

Out-of-Distribution Detection

Positional Normalization

2 code implementations NeurIPS 2019 Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge Belongie

A popular method to reduce the training time of deep neural networks is to normalize activations at each layer.

FastFusionNet: New State-of-the-Art for DAWNBench SQuAD

2 code implementations28 Feb 2019 Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger

In this technical report, we introduce FastFusionNet, an efficient variant of FusionNet [12].

Reading Comprehension

Benchmarking Single Image Dehazing and Beyond

1 code implementation12 Dec 2017 Boyi Li, Wenqi Ren, Dengpan Fu, DaCheng Tao, Dan Feng, Wen-Jun Zeng, Zhangyang Wang

We present a comprehensive study and evaluation of existing single image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy images, called REalistic Single Image DEhazing (RESIDE).

Image Dehazing Single Image Dehazing

AOD-Net: All-In-One Dehazing Network

1 code implementation ICCV 2017 Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng

This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net).

Image Dehazing Object Detection +1

End-to-End United Video Dehazing and Detection

no code implementations12 Sep 2017 Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng

Furthermore, we build an End-to-End United Video Dehazing and Detection Network(EVDD-Net), which concatenates and jointly trains EVD-Net with a video object detection model.

Image Dehazing Video Object Detection

An All-in-One Network for Dehazing and Beyond

3 code implementations20 Jul 2017 Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, Dan Feng

This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net).

Image Dehazing Object Detection +1

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