Zobrazeno 1 - 10
of 51
pro vyhledávání: '"De, Kanjar"'
Autor:
Chippa, Meenakshi Subhash, Chhipa, Prakash Chandra, De, Kanjar, Liwicki, Marcus, Saini, Rajkumar
Perspective distortion (PD) leads to substantial alterations in the shape, size, orientation, angles, and spatial relationships of visual elements in images. Accurately determining camera intrinsic and extrinsic parameters is challenging, making it h
Externí odkaz:
http://arxiv.org/abs/2410.03686
Autor:
Smirnov, Maksim, Gushchin, Aleksandr, Antsiferova, Anastasia, Vatolin, Dmitry, Timofte, Radu, Jia, Ziheng, Zhang, Zicheng, Sun, Wei, Qian, Jiaying, Cao, Yuqin, Sun, Yinan, Zhu, Yuxin, Min, Xiongkuo, Zhai, Guangtao, De, Kanjar, Luo, Qing, Zhang, Ao-Xiang, Zhang, Peng, Lei, Haibo, Jiang, Linyan, Li, Yaqing, Meng, Wenhui, Chen, Zhenzhong, Cheng, Zhengxue, Xiao, Jiahao, Xu, Jun, He, Chenlong, Zheng, Qi, Zhu, Ruoxi, Li, Min, Fan, Yibo, Tu, Zhengzhong
Video quality assessment (VQA) is a crucial task in the development of video compression standards, as it directly impacts the viewer experience. This paper presents the results of the Compressed Video Quality Assessment challenge, held in conjunctio
Externí odkaz:
http://arxiv.org/abs/2408.11982
Autor:
Chhipa, Prakash Chandra, De, Kanjar, Chippa, Meenakshi Subhash, Saini, Rajkumar, Liwicki, Marcus
The challenge of Out-Of-Distribution (OOD) robustness remains a critical hurdle towards deploying deep vision models. Vision-Language Models (VLMs) have recently achieved groundbreaking results. VLM-based open-vocabulary object detection extends the
Externí odkaz:
http://arxiv.org/abs/2405.14874
Autor:
Chhipa, Prakash Chandra, Chippa, Meenakshi Subhash, De, Kanjar, Saini, Rajkumar, Liwicki, Marcus, Shah, Mubarak
Perspective distortion (PD) causes unprecedented changes in shape, size, orientation, angles, and other spatial relationships of visual concepts in images. Precisely estimating camera intrinsic and extrinsic parameters is a challenging task that prev
Externí odkaz:
http://arxiv.org/abs/2405.02296
Autor:
Chhipa, Prakash Chandra, Holmgren, Johan Rodahl, De, Kanjar, Saini, Rajkumar, Liwicki, Marcus
Self-supervised learning in computer vision aims to leverage the inherent structure and relationships within data to learn meaningful representations without explicit human annotation, enabling a holistic understanding of visual scenes. Robustness in
Externí odkaz:
http://arxiv.org/abs/2308.02525
Autor:
Wilson, Holly, Wellington, Scott, Liwicki, Foteini Simistira, Gupta, Vibha, Saini, Rajkumar, De, Kanjar, Abid, Nosheen, Rakesh, Sumit, Eriksson, Johan, Watts, Oliver, Chen, Xi, Golbabaee, Mohammad, Proulx, Michael J., Liwicki, Marcus, O'Neill, Eamonn, Metcalfe, Benjamin
Decoding inner speech from the brain signal via hybridisation of fMRI and EEG data is explored to investigate the performance benefits over unimodal models. Two different bimodal fusion approaches are examined: concatenation of probability vectors ou
Externí odkaz:
http://arxiv.org/abs/2306.10854
Autor:
Mokayed, Hamam, Nayebiastaneh, Amirhossein, De, Kanjar, Sozos, Stergios, Hagner, Olle, Backe, Bjorn
Vehicle detection and recognition in drone images is a complex problem that has been used for different safety purposes. The main challenge of these images is captured at oblique angles and poses several challenges like non-uniform illumination effec
Externí odkaz:
http://arxiv.org/abs/2304.14466
Autor:
Chhipa, Prakash Chandra, Chopra, Muskaan, Mengi, Gopal, Gupta, Varun, Upadhyay, Richa, Chippa, Meenakshi Subhash, De, Kanjar, Saini, Rajkumar, Uchida, Seiichi, Liwicki, Marcus
This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge transfer is achieved by joint optimization of self-supervised learning ps
Externí odkaz:
http://arxiv.org/abs/2304.01354
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Recommendation systems are important intelligent systems that play a vital role in providing selective information to users. Traditional approaches in recommendation systems include collaborative filtering and content-based filtering. However, these
Externí odkaz:
http://arxiv.org/abs/1811.10804