research
∙
07/14/2023
Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images
Pathological anomalies exhibit diverse appearances in medical imaging, m...
share
research
∙
12/09/2022
Audiovisual Masked Autoencoders
Can we leverage the audiovisual information already present in video to ...
research
∙
10/22/2022
Diversity-Promoting Ensemble for Medical Image Segmentation
Medical image segmentation is an actively studied task in medical imagin...
research
∙
07/16/2022
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
A self-supervised multi-task learning (SSMTL) framework for video anomal...
research
∙
04/08/2022
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-Resolution
Super-resolving medical images can help physicians in providing more acc...
research
∙
02/10/2022
Feature-level augmentation to improve robustness of deep neural networks to affine transformations
Recent studies revealed that convolutional neural networks do not genera...
research
∙
11/20/2021
Teacher-Student Training and Triplet Loss to Reduce the Effect of Drastic Face Occlusion
We study a series of recognition tasks in two realistic scenarios requir...
research
∙
11/16/2021
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection
Detecting abnormal events in video is commonly framed as a one-class cla...
research
∙
10/12/2021
CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation
We propose a novel approach to translate unpaired contrast computed tomo...
research
∙
09/03/2021
A realistic approach to generate masked faces applied on two novel masked face recognition data sets
The COVID-19 pandemic raises the problem of adapting face recognition sy...
research
∙
08/17/2021
Contextual Convolutional Neural Networks
We propose contextual convolution (CoConv) for visual recognition. CoCon...
research
∙
11/15/2020
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning
Anomaly detection in video is a challenging computer vision problem. Due...
research
∙
09/25/2020
SuPEr-SAM: Using the Supervision Signal from a Pose Estimator to Train a Spatial Attention Module for Personal Protective Equipment Recognition
We propose a deep learning method to automatically detect personal prote...
research
∙
08/27/2020
A Scene-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video
Abnormal event detection in video is a complex computer vision problem t...
research
∙
08/03/2020
Teacher-Student Training and Triplet Loss for Facial Expression Recognition under Occlusion
In this paper, we study the task of facial expression recognition under ...
research
∙
02/02/2020
Non-linear Neurons with Human-like Apical Dendrite Activations
In order to classify linearly non-separable data, neurons are typically ...
research
∙
01/05/2020
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI Scans
CT scanners that are commonly-used in hospitals nowadays produce low-res...
research
∙
11/12/2019
Recognizing Facial Expressions of Occluded Faces using Convolutional Neural Networks
In this paper, we present an approach based on convolutional neural netw...
research
∙
05/02/2019
Clustering Images by Unmasking - A New Baseline
We propose a novel agglomerative clustering method based on unmasking, a...
research
∙
12/11/2018
Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video
Abnormal event detection in video is a challenging vision problem. Most ...
research
∙
04/29/2018
