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20172021
most citedThe Devil Is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection

19 citations · 47 across the 14 of their papers we have counts for

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12 papers · 1 filter

cs.CV20212 cited

Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction

Xiangnan Yin, Di Huang, Zehua Fu +2

Although much progress has been made recently in 3D face reconstruction, most previous work has been devoted to predicting accurate and fine-grained 3D shapes. In contrast, relativ…

cs.CV20211 cited

Pixel Sampling for Style Preserving Face Pose Editing

Xiangnan Yin, Di Huang, Hongyu Yang +3

The existing auto-encoder based face pose editing methods primarily focus on modeling the identity preserving ability during pose synthesis, but are less able to preserve the image…

cs.CV2021

Connecting Images through Time and Sources: Introducing Low-data, Heterogeneous Instance Retrieval

Dimitri Gominski, Valérie Gouet-Brunet, Liming Chen

With impressive results in applications relying on feature learning, deep learning has also blurred the line between algorithm and data. Pick a training dataset, pick a backbone ne…

cs.CV20211 cited

Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation

Lingkun Luo, Liming Chen, Shiqiang Hu

Domain adaptation (DA) aims to enable a learning model trained from a source domain to generalize well on a target domain, despite the mismatch of data distributions between the tw…

cs.CV20201 cited

An Assessment of GANs for Identity-related Applications

Richard T. Marriott, Safa Madiouni, Sami Romdhani +2

Generative Adversarial Networks (GANs) are now capable of producing synthetic face images of exceptionally high visual quality. In parallel to the development of GANs themselves, e…

cs.CV20201 cited

Robustness of Facial Recognition to GAN-based Face-morphing Attacks

Richard T. Marriott, Sami Romdhani, Stéphane Gentric +1

Face-morphing attacks have been a cause for concern for a number of years. Striving to remain one step ahead of attackers, researchers have proposed many methods of both creating a…