Search Results for author: M. Ozan Tezcan

Found 4 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.

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

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