37 citations · 97 across the 8 of their papers we have counts for
9 papers
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…
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,…
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…
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…
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…
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…
Clustering and Unsupervised Anomaly Detection with L2 Normalized Deep Auto-Encoder Representations
Caglar Aytekin, Xingyang Ni, Francesco Cricri +1
Clustering is essential to many tasks in pattern recognition and computer vision. With the advent of deep learning, there is an increasing interest in learning deep unsupervised re…
Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels
Caglar Aytekin, Xingyang Ni, Francesco Cricri +2
Computer vision algorithms with pixel-wise labeling tasks, such as semantic segmentation and salient object detection, have gone through a significant accuracy increase with the in…
Video Ladder Networks
Francesco Cricri, Xingyang Ni, Mikko Honkala +2
We present the Video Ladder Network (VLN) for efficiently generating future video frames. VLN is a neural encoder-decoder model augmented at all layers by both recurrent and feedfo…