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20182021
most citedAll-In-One Underwater Image Enhancement using Domain-Adversarial Learning

74 citations · 92 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV20207 cited

MM-Hand: 3D-Aware Multi-Modal Guided Hand Generative Network for 3D Hand Pose Synthesis

Zhenyu Wu, Duc Hoang, Shih-Yao Lin +5

Estimating the 3D hand pose from a monocular RGB image is important but challenging. A solution is training on large-scale RGB hand images with accurate 3D hand keypoint annotation…

cs.CV2019

Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach

Zhenyu Wu, Karthik Suresh, Priya Narayanan +3

Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. Despite the great success of the generic object detection methods trained…

cs.CV2019

Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset

Zhenyu Wu, Haotao Wang, Zhaowen Wang +2

We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications. A novel adversarial training fra…

cs.CV201974 cited

All-In-One Underwater Image Enhancement using Domain-Adversarial Learning

Pritish Uplavikar, Zhenyu Wu, Zhangyang Wang

Raw underwater images are degraded due to wavelength dependent light attenuation and scattering, limiting their applicability in vision systems. Another factor that makes enhancing…

cs.CV2018

Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study

Zhenyu Wu, Zhangyang Wang, Zhaowen Wang +1

This paper aims to improve privacy-preserving visual recognition, an increasingly demanded feature in smart camera applications, by formulating a unique adversarial training framew…