Search Results for author: Thomas Leung

Found 10 papers, 4 papers with code

Geo-Aware Networks for Fine-Grained Recognition

1 code implementation4 Jun 2019 Grace Chu, Brian Potetz, Weijun Wang, Andrew Howard, Yang song, Fernando Brucher, Thomas Leung, Hartwig Adam

By leveraging geolocation information we improve top-1 accuracy in iNaturalist from 70. 1% to 79. 0% for a strong baseline image-only model.

Fine-Grained Image Classification General Classification

Towards a Semantic Perceptual Image Metric

no code implementations1 Aug 2018 Troy Chinen, Johannes Ballé, Chunhui Gu, Sung Jin Hwang, Sergey Ioffe, Nick Johnston, Thomas Leung, David Minnen, Sean O'Malley, Charles Rosenberg, George Toderici

We present a full reference, perceptual image metric based on VGG-16, an artificial neural network trained on object classification.

Image Quality Assessment

Improving the Robustness of Deep Neural Networks via Stability Training

no code implementations CVPR 2016 Stephan Zheng, Yang song, Thomas Leung, Ian Goodfellow

In this paper we address the issue of output instability of deep neural networks: small perturbations in the visual input can significantly distort the feature embeddings and output of a neural network.

General Classification

MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching

2 code implementations CVPR 2015 Xufeng Han, Thomas Leung, Yangqing Jia, Rahul Sukthankar, Alexander C. Berg

We perform a comprehensive set of experiments on standard datasets to carefully study the contributions of each aspect of MatchNet, with direct comparisons to established methods.

Metric Learning Patch Matching

Large-Scale Video Classification with Convolutional Neural Networks

no code implementations 2014 IEEE Conference on Computer Vision and Pattern Recognition 2014 Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, Li Fei-Fei

We further study the generalization performance of our best model by retraining the top layers on the UCF-101 Action Recognition dataset and observe significant performance improvements compared to the UCF-101 baseline model (63. 3% up from 43. 9%).

Action Recognition Classification +3

Learning Fine-grained Image Similarity with Deep Ranking

6 code implementations CVPR 2014 Jiang Wang, Yang song, Thomas Leung, Chuck Rosenberg, Jinbin Wang, James Philbin, Bo Chen, Ying Wu

This paper proposes a deep ranking model that employs deep learning techniques to learn similarity metric directly from images. It has higher learning capability than models based on hand-crafted features.

General Classification

Deep Convolutional Ranking for Multilabel Image Annotation

no code implementations17 Dec 2013 Yunchao Gong, Yangqing Jia, Thomas Leung, Alexander Toshev, Sergey Ioffe

Multilabel image annotation is one of the most important challenges in computer vision with many real-world applications.

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