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Zero-Shot and Few-Shot Video Question Answering with Multi-Modal Prompts
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Year: 2023 | Conference Paper |
Recent vision-language models are driven by large-scale pretrained models. However, adapting pretrained models on limited data presents challenges such as overfitting, catastrophic forgetting, and the cross-modal gap between vision and language. We introduce a parameter-efficient method to address these challenges, combining multimodal prompt learning and a transformer-based mapping network, while...Show More
On the hidden treasure of dialog in video question answering
Deniz Engin;François Schnitzler;Ngoc Q. K. Duong;Yannis Avrithis
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
High-level understanding of stories in video such as movies and TV shows from raw data is extremely challenging. Modern video question answering (VideoQA) systems often use additional human-made sources like plot synopses, scripts, video descriptions or knowledge bases. In this work, we present a new approach to understand the whole story without such external sources. The secret lies in the dialo...Show More
Offline Signature Verification on Real-World Documents
Deniz Engin;Alperen Kantarcı;Seçil Arslan;Hazım Kemal Ekenel
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2020 | Conference Paper |
Cited by: Papers (13)
Research on offline signature verification has explored a large variety of methods on multiple signature datasets, which are collected under controlled conditions. However, these datasets may not fully reflect the characteristics of the signatures in some practical use cases. Real-world signatures extracted from the formal documents may contain different types of occlusions, for example, stamps, c...Show More
A Semi-Automatic Annotation Interface for Named Entity and Relation Annotation on Document Images
Mehmet Yasin Akpınar;Berke Oral;Deniz Engin;Erdem Emekligil;Seçil Arslan;Gülşen Eryiğit
2019 4th International Conference on Computer Science and Engineering (UBMK)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
To be able to use supervised machine learning methods in natural language processing, there is a need of labeled data in large quantities. In some cases, especially when there are multiple tasks conducted on the same data, the annotation process may become exhausting and time consuming for both the annotatore and interpreters. Thus, an effective annotation tool becomes crucial in order to both inc...Show More
NTIRE 2018 Challenge on Image Dehazing: Methods and Results
Cosmin Ancuti;Codruta O. Ancuti;Radu Timofte;Luc Van Gool;Lei Zhang;Ming-Hsuan Yang;Vishal M. Patel;He Zhang;Vishwanath A. Sindagi;Ruhao Zhao;Xiaoping Ma;Yong Qin;Limin Jia;Klaus Friedel;Sehwan Ki;Hyeonjun Sim;Jae-Seok Choi;Sooye Kim;Soomin Seo;Saehun Kim;Munchurl Kim;Ranjan Mondal;Sanchayan Santra;Bhabatosh Chanda;Jinlin Liu;Kangfu Mei;Juncheng Li;Luyao;Faming Fang;Aiwen Jiang;Xiaochao Qu;Ting Liu;Pengfei Wang;Biao Sun;Jiangfan Deng;Yuhang Zhao;Ming Hong;Jingying Huang;Yizhi Chen;Erin Chen;Xiaoli Yu;Tingting Wu;Anil Genc;Deniz Engin;Hazim Kemal Ekenel;Wenzhe Liu;Tong Tong;Gen Li;Qinquan Gao;Zhan Li;Daofa Tang;Yuling Chen;Ziying Huo;Aitor Alvarez-Gila;Adrian Galdran;Alessandro Bria;Javier Vazquez-Corral;Marcelo Bertalmo;H. Seckin Demir;Omer Faruk Adil;Huynh Xuan Phung;Xin Jin;Jiale Chen;Chaowei Shan;Zhibo Chen
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2018 | Conference Paper |
Cited by: Papers (87)
This paper reviews the first challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results. The challenge had 2 tracks. Track 1 employed the indoor images (using I-HAZE dataset), while Track 2 outdoor images (using O-HAZE dataset). The hazy images have been captured in presence of real haze, generated by professional haze machines. I-HAZE data...Show More
NTIRE 2018 Challenge on Image Dehazing: Methods and Results
Cosmin Ancuti;Codruta O. Ancuti;Radu Timofte;Luc Van Gool;Lei Zhang;Ming-Hsuan Yang;Vishal M. Patel;He Zhang;Vishwanath A. Sindagi;Ruhao Zhao;Xiaoping Ma;Yong Qin;Limin Jia;Klaus Friedel;Sehwan Ki;Hyeonjun Sim;Jae-Seok Choi;Sooye Kim;Soomin Seo;Saehun Kim;Munchurl Kim;Ranjan Mondal;Sanchayan Santra;Bhabatosh Chanda;Jinlin Liu;Kangfu Mei;Juncheng Li;Luyao;Faming Fang;Aiwen Jiang;Xiaochao Qu;Ting Liu;Pengfei Wang;Biao Sun;Jiangfan Deng;Yuhang Zhao;Ming Hong;Jingying Huang;Yizhi Chen;Erin Chen;Xiaoli Yu;Tingting Wu;Anil Genc;Deniz Engin;Hazim Kemal Ekenel;Wenzhe Liu;Tong Tong;Gen Li;Qinquan Gao;Zhan Li;Daofa Tang;Yuling Chen;Ziying Huo;Aitor Alvarez-Gila;Adrian Galdran;Alessandro Bria;Javier Vazquez-Corral;Marcelo Bertalmo;H. Seckin Demir;Omer Faruk Adil;Huynh Xuan Phung;Xin Jin;Jiale Chen;Chaowei Shan;Zhibo Chen
Year: 2018 | Conference Paper |
Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2018 | Conference Paper |
Cited by: Papers (401)
In this paper, we present an end-to-end network, called Cycle-Dehaze, for single image dehazing problem, which does not require pairs of hazy and corresponding ground truth images for training. That is, we train the network by feeding clean and hazy images in an unpaired manner. Moreover, the proposed approach does not rely on estimation of the atmospheric scattering model parameters. Our method e...Show More
Face Frontalization for Cross-Pose Facial Expression Recognition
Deniz Engin;Christophe Ecabert;Hazim Kemal Ekenel;Jean-Philippe Thiran
2018 26th European Signal Processing Conference (EUSIPCO)
Year: 2018 | Conference Paper |
Cited by: Papers (2)
In this paper, we have explored the effect of pose normalization for cross-pose facial expression recognition. We have first presented an expression preserving face frontalization method. After face frontalization step, for facial expression representation and classification, we have employed both a traditional approach, by using hand-crafted features, namely local binary patterns, in combination ...Show More
Facial expression pair matching
Deniz Engin;Hazım Kemal Ekenel;Bilgisayar Mühendisliği Bölümü
2017 25th Signal Processing and Communications Applications Conference (SIU)
Year: 2017 | Conference Paper |
In this study, facial expression recognition is defined as a pair matching problem. Our objectives to formulate this talk in this way are to be able to decide whether the facial expressions of the unlabeled images of two people are the same or different and to benefit from the proposed pair matching methods that have been studied for many years in the face recognition field. The Extended Cohn-Kana...Show More
Implementation of Enigma machine using verilog on an FPGA
2015 9th International Conference on Electrical and Electronics Engineering (ELECO)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
The Enigma machine was used in the twentieth century for enciphering and deciphering secret messages. It has been implemented on an Field Programmable Gate Array (FPGA) in this paper. The Enigma machine is kind of poly alphabetic cipher. In other words, even if input is the same letter, output can be a different letter. Therefore, the Enigma machine can not be broken by using easy methods of crypt...Show More
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