Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Bandara, Wele Gedara Chaminda"'
In this paper, we introduce Attention Prompt Tuning (APT) - a computationally efficient variant of prompt tuning for video-based applications such as action recognition. Prompt tuning approaches involve injecting a set of learnable prompts along with
Externí odkaz:
http://arxiv.org/abs/2403.06978
Self-supervised Learning (SSL) aims to learn transferable feature representations for downstream applications without relying on labeled data. The Barlow Twins algorithm, renowned for its widespread adoption and straightforward implementation compare
Externí odkaz:
http://arxiv.org/abs/2312.02151
Autor:
Ranasinghe, Yasiru, Nair, Nithin Gopalakrishnan, Bandara, Wele Gedara Chaminda, Patel, Vishal M.
Crowd counting is a fundamental problem in crowd analysis which is typically accomplished by estimating a crowd density map and summing over the density values. However, this approach suffers from background noise accumulation and loss of density due
Externí odkaz:
http://arxiv.org/abs/2303.12790
Remote Sensing Change Detection (RS-CD) aims to detect relevant changes from Multi-Temporal Remote Sensing Images (MT-RSIs), which aids in various RS applications such as land cover, land use, human development analysis, and disaster response. The pe
Externí odkaz:
http://arxiv.org/abs/2303.09536
Generating photos satisfying multiple constraints find broad utility in the content creation industry. A key hurdle to accomplishing this task is the need for paired data consisting of all modalities (i.e., constraints) and their corresponding output
Externí odkaz:
http://arxiv.org/abs/2212.00793
Autor:
Bandara, Wele Gedara Chaminda, Patel, Naman, Gholami, Ali, Nikkhah, Mehdi, Agrawal, Motilal, Patel, Vishal M.
Masked Autoencoders (MAEs) learn generalizable representations for image, text, audio, video, etc., by reconstructing masked input data from tokens of the visible data. Current MAE approaches for videos rely on random patch, tube, or frame-based mask
Externí odkaz:
http://arxiv.org/abs/2211.09120
Remote sensing change detection is crucial for understanding the dynamics of our planet's surface, facilitating the monitoring of environmental changes, evaluating human impact, predicting future trends, and supporting decision-making. In this work,
Externí odkaz:
http://arxiv.org/abs/2206.11892
Autor:
Rahman, Aimon, Bandara, Wele Gedara Chaminda, Valanarasu, Jeya Maria Jose, Hacihaliloglu, Ilker, Patel, Vishal M
Due to imaging artifacts and low signal-to-noise ratio in ultrasound images, automatic bone surface segmentation networks often produce fragmented predictions that can hinder the success of ultrasound-guided computer-assisted surgical procedures. Exi
Externí odkaz:
http://arxiv.org/abs/2206.08481
Image synthesis under multi-modal priors is a useful and challenging task that has received increasing attention in recent years. A major challenge in using generative models to accomplish this task is the lack of paired data containing all modalitie
Externí odkaz:
http://arxiv.org/abs/2206.05039
Autor:
Perera, Malsha V., Nair, Nithin Gopalakrishnan, Bandara, Wele Gedara Chaminda, Patel, Vishal M.
Speckle is a multiplicative noise which affects all coherent imaging modalities including Synthetic Aperture Radar (SAR) images. The presence of speckle degrades the image quality and adversely affects the performance of SAR image understanding appli
Externí odkaz:
http://arxiv.org/abs/2206.04514