7 citations · 13 across the 8 of their papers we have counts for
8 papers
Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training
Jeya Maria Jose Valanarasu, Yucheng Tang, Dong Yang +8
Harnessing the power of pre-training on large-scale datasets like ImageNet forms a fundamental building block for the progress of representation learning-driven solutions in comput…
ReBotNet: Fast Real-time Video Enhancement
Jeya Maria Jose Valanarasu, Rahul Garg, Andeep Toor +5
Most video restoration networks are slow, have high computational load, and can't be used for real-time video enhancement. In this work, we design an efficient and fast framework t…
Orientation-guided Graph Convolutional Network for Bone Surface Segmentation
Aimon Rahman, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu +2
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 s…
SAR Despeckling Using Overcomplete Convolutional Networks
Malsha V. Perera, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu +1
Synthetic Aperture Radar (SAR) despeckling is an important problem in remote sensing as speckle degrades SAR images, affecting downstream tasks like detection and segmentation. Rec…
Interactive Portrait Harmonization
Jeya Maria Jose Valanarasu, He Zhang, Jianming Zhang +7
Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/…
Transformer-based SAR Image Despeckling
Malsha V. Perera, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu +1
Synthetic Aperture Radar (SAR) images are usually degraded by a multiplicative noise known as speckle which makes processing and interpretation of SAR images difficult. In this pap…
Fine-Context Shadow Detection using Shadow Removal
Jeya Maria Jose Valanarasu, Vishal M. Patel
Current shadow detection methods perform poorly when detecting shadow regions that are small, unclear or have blurry edges. In this work, we attempt to address this problem on two…
Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction
Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu, Vishal M. Patel
Hyperspectral pansharpening aims to synthesize a low-resolution hyperspectral image (LR-HSI) with a registered panchromatic image (PAN) to generate an enhanced HSI with high spectr…