1 code implementation • 13 Dec 2023 • Amirhossein Habibian, Amir Ghodrati, Noor Fathima, Guillaume Sautiere, Risheek Garrepalli, Fatih Porikli, Jens Petersen
This work aims to improve the efficiency of text-to-image diffusion models.
no code implementations • 5 Jan 2023 • Shashanka Venkataramanan, Amir Ghodrati, Yuki M. Asano, Fatih Porikli, Amirhossein Habibian
This work aims to improve the efficiency of vision transformers (ViT).
no code implementations • 5 Apr 2022 • Babak Ehteshami Bejnordi, Amirhossein Habibian, Fatih Porikli, Amir Ghodrati
In this paper, we propose SALISA, a novel non-uniform SALiency-based Input SAmpling technique for video object detection that allows for heavy down-sampling of unimportant background regions while preserving the fine-grained details of a high-resolution image.
1 code implementation • CVPR 2021 • Amir Ghodrati, Babak Ehteshami Bejnordi, Amirhossein Habibian
In this paper, we propose a conditional early exiting framework for efficient video recognition.
no code implementations • 18 Jul 2018 • Amir Ghodrati, Efstratios Gavves, Cees G. M. Snoek
Time-aware encoding of frame sequences in a video is a fundamental problem in video understanding.
1 code implementation • CVPR 2018 • Kirill Gavrilyuk, Amir Ghodrati, Zhenyang Li, Cees G. M. Snoek
This paper strives for pixel-level segmentation of actors and their actions in video content.
Ranked #13 on Referring Expression Segmentation on J-HMDB
1 code implementation • 15 Jun 2016 • Amir Ghodrati, Ali Diba, Marco Pedersoli, Tinne Tuytelaars, Luc van Gool
In this paper, a new method for generating object and action proposals in images and videos is proposed.
no code implementations • 21 Apr 2016 • Roeland De Geest, Efstratios Gavves, Amir Ghodrati, Zhenyang Li, Cees Snoek, Tinne Tuytelaars
Third, the start of the action is unknown, so it is unclear over what time window the information should be integrated.
1 code implementation • 6 Dec 2015 • Basura Fernando, Efstratios Gavves, Jose Oramas, Amir Ghodrati, Tinne Tuytelaars
We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation.
no code implementations • 26 Nov 2015 • Amir Ghodrati, Xu Jia, Marco Pedersoli, Tinne Tuytelaars
Learning the distribution of images in order to generate new samples is a challenging task due to the high dimensionality of the data and the highly non-linear relations that are involved.
1 code implementation • ICCV 2015 • Amir Ghodrati, Ali Diba, Marco Pedersoli, Tinne Tuytelaars, Luc van Gool
We generate hypotheses in a sliding-window fashion over different activation layers and show that the final convolutional layers can find the object of interest with high recall but poor localization due to the coarseness of the feature maps.
no code implementations • CVPR 2015 • Basura Fernando, Efstratios Gavves, Jose Oramas M., Amir Ghodrati, Tinne Tuytelaars
We postulate that a function capable of ordering the frames of a video temporally (based on the appearance) captures well the evolution of the appearance within the video.