no code implementations • 3 Jan 2024 • Samhita Kuili, Kareem Dabbour, Irtiza Hasan, Andrea Herscovich, Burak Kantarci, Marcel Chenier, Melike Erol-Kantarci
Data privacy and protection through anonymization is a critical issue for network operators or data owners before it is forwarded for other possible use of data.
1 code implementation • 3 Mar 2023 • Animesh Gupta, Irtiza Hasan, Dilip K. Prasad, Deepak K. Gupta
We further show that when no pretraining is done or when the pretrained transformer models are used with non-natural images (e. g. medical data), CNNs tend to generalize better than transformers at even very small coreset sizes.
Ranked #3 on Image Classification on Tiny ImageNet Classification
no code implementations • 22 Mar 2022 • Luca Franco, Leonardo Placidi, Francesco Giuliari, Irtiza Hasan, Marco Cristani, Fabio Galasso
This paper proposes the first in-depth study of Transformer Networks (TF) and Bidirectional Transformers (BERT) for the forecasting of the individual motion of people, without bells and whistles.
2 code implementations • 10 Jan 2022 • Irtiza Hasan, Shengcai Liao, Jinpeng Li, Saad Ullah Akram, Ling Shao
As for the data, we show that the autonomous driving benchmarks are monotonous in nature, that is, they are not diverse in scenarios and dense in pedestrians.
no code implementations • 17 Apr 2020 • Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Alessio Del Bue, Fabio Galasso
Illumination is important for well-being, productivity and safety across several environments, including offices, retail shops and industrial warehouses.
1 code implementation • CVPR 2021 • Irtiza Hasan, Shengcai Liao, Jinpeng Li, Saad Ullah Akram, Ling Shao
Furthermore, we illustrate that diverse and dense datasets, collected by crawling the web, serve to be an efficient source of pre-training for pedestrian detection.
Ranked #3 on Pedestrian Detection on CityPersons (using extra training data)
1 code implementation • 18 Mar 2020 • Francesco Giuliari, Irtiza Hasan, Marco Cristani, Fabio Galasso
In particular, the TF model without bells and whistles yields the best score on the largest and most challenging trajectory forecasting benchmark of TrajNet.
Ranked #11 on Trajectory Prediction on ETH/UCY
2 code implementations • CVPR 2019 • Wei Liu, Irtiza Hasan, Shengcai Liao
Like edges, corners, blobs and other feature detectors, the proposed detector scans for feature points all over the image, for which the convolution is naturally suited.
Ranked #8 on Pedestrian Detection on Caltech (using extra training data)
no code implementations • 30 Jan 2019 • Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Alessio Del Bue, Fabio Galasso
ILS may therefore dim those luminaires, which are not seen by the user, resulting in an effective energy saving, especially in large open offices (where light may otherwise be ON everywhere for a single person).
no code implementations • 7 Jan 2019 • Irtiza Hasan, Francesco Setti, Theodore Tsesmelis, Vasileios Belagiannis, Sikandar Amin, Alessio Del Bue, Marco Cristani, Fabio Galasso
In this work, we explore the correlation between people trajectories and their head orientations.
no code implementations • 20 Sep 2018 • Theodore Tsesmelis, Irtiza Hasan, Marco Cristani, Fabio Galasso, Alessio Del Bue
The proposed method uses both depth data and images from the sensor to provide a dense measure of light intensity in the field of view of the camera.
no code implementations • CVPR 2018 • Irtiza Hasan, Francesco Setti, Theodore Tsesmelis, Alessio Del Bue, Fabio Galasso, Marco Cristani
Recent approaches on trajectory forecasting use tracklets to predict the future positions of pedestrians exploiting Long Short Term Memory (LSTM) architectures.
no code implementations • IEEE Winter Conference on Applications of Computer Vision (WACV) 2018 • Irtiza Hasan, Francesco Setti, Theodore Tsesmelis, Alessio Del Bue, Marco Cristani, Fabio Galasso
In this paper we show the importance of the head pose estimation in the task of trajectory forecasting.