activity
20182021
most citedVehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification

27 citations · 27 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Towards a Real-Time Facial Analysis System

Bishwo Adhikari, Xingyang Ni, Esa Rahtu +1

Facial analysis is an active research area in computer vision, with many practical applications. Most of the existing studies focus on addressing one specific task and maximizing i…

cs.CV2021

On the Importance of Encrypting Deep Features

Xingyang Ni, Heikki Huttunen, Esa Rahtu

In this study, we analyze model inversion attacks with only two assumptions: feature vectors of user data are known, and a black-box API for inference is provided. On the one hand,…

cs.CV2021

FlipReID: Closing the Gap between Training and Inference in Person Re-Identification

Xingyang Ni, Esa Rahtu

Since neural networks are data-hungry, incorporating data augmentation in training is a widely adopted technique that enlarges datasets and improves generalization. On the other ha…

cs.CV2020

Adaptive L2 Regularization in Person Re-Identification

Xingyang Ni, Liang Fang, Heikki Huttunen

We introduce an adaptive L2 regularization mechanism in the setting of person re-identification. In the literature, it is common practice to utilize hand-picked regularization fact…

cs.CV202027 cited

Vehicle Attribute Recognition by Appearance: Computer Vision Methods for Vehicle Type, Make and Model Classification

Xingyang Ni, Heikki Huttunen

This paper studies vehicle attribute recognition by appearance. In the literature, image-based target recognition has been extensively investigated in many use cases, such as facia…

cs.LG2018

Block-optimized Variable Bit Rate Neural Image Compression

Caglar Aytekin, Xingyang Ni, Francesco Cricri +3

In this work, we propose an end-to-end block-based auto-encoder system for image compression. We introduce novel contributions to neural-network based image compression, mainly in…