output
20022023
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing cs.CVShow all

12 papers · 1 filter

cs.CV202340 cited

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…

cs.CV20214 cited

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…

cs.CV2021

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…

cs.CV202148 cited

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…

cs.CV20204 cited

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…

cs.CV2020

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…