37 citations · 63 across the 15 of their papers we have counts for
11 papers · 1 filter
SceneHI: High-Resolution 3D-Consistent Scene Texturing with Controllable Illumination
Athanasios Tragakis, Marco Aversa, Daniela Ivanova +4
SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first to demonstrate that high-reso…
IGAF: Incremental Guided Attention Fusion for Depth Super-Resolution
Athanasios Tragakis, Chaitanya Kaul, Kevin J. Mitchell +3
Accurate depth estimation is crucial for many fields, including robotics, navigation, and medical imaging. However, conventional depth sensors often produce low-resolution (LR) dep…
HpEIS: Learning Hand Pose Embeddings for Multimedia Interactive Systems
Songpei Xu, Xuri Ge, Chaitanya Kaul +1
We present a novel Hand-pose Embedding Interactive System (HpEIS) as a virtual sensor, which maps users' flexible hand poses to a two-dimensional visual space using a Variational A…
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models
Athanasios Tragakis, Marco Aversa, Chaitanya Kaul +2
In this work, we introduce Pixelsmith, a zero-shot text-to-image generative framework to sample images at higher resolutions with a single GPU. We are the first to show that it is…
GLFNET: Global-Local (frequency) Filter Networks for efficient medical image segmentation
Athanasios Tragakis, Qianying Liu, Chaitanya Kaul +5
We propose a novel transformer-style architecture called Global-Local Filter Network (GLFNet) for medical image segmentation and demonstrate its state-of-the-art performance. We re…
Optimizing Vision Transformers for Medical Image Segmentation
Qianying Liu, Chaitanya Kaul, Jun Wang +3
For medical image semantic segmentation (MISS), Vision Transformers have emerged as strong alternatives to convolutional neural networks thanks to their inherent ability to capture…
Rotation Equivariant 3D Hand Mesh Generation from a Single RGB Image
Joshua Mitton, Chaitanya Kaul, Roderick Murray-Smith
We develop a rotation equivariant model for generating 3D hand meshes from 2D RGB images. This guarantees that as the input image of a hand is rotated the generated mesh undergoes…
CpT: Convolutional Point Transformer for 3D Point Cloud Processing
Chaitanya Kaul, Joshua Mitton, Hang Dai +1
We present CpT: Convolutional point Transformer - a novel deep learning architecture for dealing with the unstructured nature of 3D point cloud data. CpT is an improvement over exi…
FatNet: A Feature-attentive Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
The application of deep learning to 3D point clouds is challenging due to its lack of order. Inspired by the point embeddings of PointNet and the edge embeddings of DGCNNs, we prop…
SAWNet: A Spatially Aware Deep Neural Network for 3D Point Cloud Processing
Chaitanya Kaul, Nick Pears, Suresh Manandhar
Deep neural networks have established themselves as the state-of-the-art methodology in almost all computer vision tasks to date. But their application to processing data lying on…
FocusNet: An attention-based Fully Convolutional Network for Medical Image Segmentation
Chaitanya Kaul, Suresh Manandhar, Nick Pears
We propose a novel technique to incorporate attention within convolutional neural networks using feature maps generated by a separate convolutional autoencoder. Our attention archi…