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20152020
most citedDeep Transfer Network: Unsupervised Domain Adaptation

126 citations · 219 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV20204 cited

Deep Learning Guided Building Reconstruction from Satellite Imagery-derived Point Clouds

Bo Xu, Xu Zhang, Zhixin Li +3

3D urban reconstruction of buildings from remotely sensed imagery has drawn significant attention during the past two decades. While aerial imagery and LiDAR provide higher resolut…

cs.CV2020

Unifying Specialist Image Embedding into Universal Image Embedding

Yang Feng, Futang Peng, Xu Zhang +7

Deep image embedding provides a way to measure the semantic similarity of two images. It plays a central role in many applications such as image search, face verification, and zero…

cs.CV2019

Detecting and Simulating Artifacts in GAN Fake Images

Xu Zhang, Svebor Karaman, Shih-Fu Chang

To detect GAN generated images, conventional supervised machine learning algorithms require collection of a number of real and fake images from the targeted GAN model. However, the…

cs.CV201979 cited

Unsupervised Embedding Learning via Invariant and Spreading Instance Feature

Mang Ye, Xu Zhang, Pong C. Yuen +1

This paper studies the unsupervised embedding learning problem, which requires an effective similarity measurement between samples in low-dimensional embedding space. Motivated by…

cs.CV201710 cited

Learning Spread-out Local Feature Descriptors

Xu Zhang, Felix X. Yu, Sanjiv Kumar +1

We propose a simple, yet powerful regularization technique that can be used to significantly improve both the pairwise and triplet losses in learning local feature descriptors. The…

cs.CV2015126 cited

Deep Transfer Network: Unsupervised Domain Adaptation

Xu Zhang, Felix Xinnan Yu, Shih-Fu Chang +1

Domain adaptation aims at training a classifier in one dataset and applying it to a related but not identical dataset. One successfully used framework of domain adaptation is to le…