Search Results for author: Janusz Konrad

Found 9 papers, 4 papers with code

BSUV-Net 2.0: Spatio-Temporal Data Augmentations for Video-Agnostic Supervised Background Subtraction

1 code implementation23 Jan 2021 M. Ozan Tezcan, Prakash Ishwar, Janusz Konrad

In this work, we introduce spatio-temporal data augmentations and apply them to one of the leading video-agnostic BGS algorithms, BSUV-Net.

RAPiD: Rotation-Aware People Detection in Overhead Fisheye Images

1 code implementation23 May 2020 Zhihao Duan, M. Ozan Tezcan, Hayato Nakamura, Prakash Ishwar, Janusz Konrad

Recent methods for people detection in overhead, fisheye images either use radially-aligned bounding boxes to represent people, assuming people always appear along image radius or require significant pre-/post-processing which radically increases computational complexity.

Low-Resolution Overhead Thermal Tripwire for Occupancy Estimation

no code implementations12 Apr 2020 Mertcan Cokbas, Prakash Ishwar, Janusz Konrad

We propose a people counting system which uses a low-resolution thermal sensor.

VAE/WGAN-Based Image Representation Learning For Pose-Preserving Seamless Identity Replacement In Facial Images

no code implementations2 Mar 2020 Hiroki Kawai, Jia-Wei Chen, Prakash Ishwar, Janusz Konrad

We present a novel variational generative adversarial network (VGAN) based on Wasserstein loss to learn a latent representation from a face image that is invariant to identity but preserves head-pose information.

Representation Learning

BSUV-Net: A Fully-Convolutional Neural Network forBackground Subtraction of Unseen Videos

1 code implementation ICCV 2020 M. Ozan Tezcan, Prakash Ishwar, Janusz Konrad

In order to reduce the chance of overfitting, we also introduce a new data-augmentation technique which mitigates the impact of illumination difference between the background frames and the current frame.

Data Augmentation Object Tracking

BSUV-Net: A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos

1 code implementation26 Jul 2019 M. Ozan Tezcan, Prakash Ishwar, Janusz Konrad

In order to reduce the chance of overfitting, we also introduce a new data-augmentation technique which mitigates the impact of illumination difference between the background frames and the current frame.

Data Augmentation Object Tracking +1

A Cyclically-Trained Adversarial Network for Invariant Representation Learning

no code implementations21 Jun 2019 Jiawei Chen, Janusz Konrad, Prakash Ishwar

Specifically, we propose a cyclically-trained adversarial network to learn a mapping from image space to latent representation space and back such that the latent representation is invariant to a specified factor of variation (e. g., identity).

Representation Learning

Semi-Coupled Two-Stream Fusion ConvNets for Action Recognition at Extremely Low Resolutions

no code implementations12 Oct 2016 Jiawei Chen, Jonathan Wu, Janusz Konrad, Prakash Ishwar

Deep convolutional neural networks (ConvNets) have been recently shown to attain state-of-the-art performance for action recognition on standard-resolution videos.

Action Recognition

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