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12 papers · 1 filter
LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar
Yuelang Xu, Hongwen Zhang, Lizhen Wang +4
Existing approaches to animatable NeRF-based head avatars are either built upon face templates or use the expression coefficients of templates as the driving signal. Despite the pr…
A two-step machine learning approach for crop disease detection: an application of GAN and UAV technology
Aaditya Prasad, Nikhil Mehta, Matthew Horak +1
Automated plant diagnosis is a technology that promises large increases in cost-efficiency for agriculture. However, multiple problems reduce the effectiveness of drones, including…
Transferable Adversarial Examples for Anchor Free Object Detection
Quanyu Liao, Xin Wang, Bin Kong +5
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbation can completely change prediction result. The vulnerability has led to a sur…
Combining pretrained CNN feature extractors to enhance clustering of complex natural images
Joris Guerin, Stephane Thiery, Eric Nyiri +2
Recently, a common starting point for solving complex unsupervised image classification tasks is to use generic features, extracted with deep Convolutional Neural Networks (CNN) pr…
Exploring Severe Occlusion: Multi-Person 3D Pose Estimation with Gated Convolution
Renshu Gu, Gaoang Wang, Jenq-Neng Hwang
3D human pose estimation (HPE) is crucial in many fields, such as human behavior analysis, augmented reality/virtual reality (AR/VR) applications, and self-driving industry. Videos…
Fast Local Attack: Generating Local Adversarial Examples for Object Detectors
Quanyu Liao, Xin Wang, Bin Kong +4
The deep neural network is vulnerable to adversarial examples. Adding imperceptible adversarial perturbations to images is enough to make them fail. Most existing research focuses…