5 papers
Learning Semantic Inpainting for Animatable Gaussian Head Avatars
Pilseo Park, Fizza Rubab, Yiying Tong
We present SInGA, a novel method for learning Semantic Inpainting for animatable Gaussian head Avatars from a single image. Existing avatar approaches often rely on multi-view obse…
Unmasking Face Embeddings: Reading, Rendering and Naming with Foundation Models
Fizza Rubab, Yiying Tong, Arun Ross
Modern face recognition (FR) owes much of its success to deep neural networks that learn to extract compact identity embeddings from face images. These models are typically trained…
Compatibility of Face Embeddings Across Deep Neural Networks
Fizza Rubab, Yiying Tong, Arun Ross
Automated face recognition has made rapid strides over the past decade due to the unprecedented rise of deep neural network (DNN) models that can be trained for domain-specific tas…
Learning Neural Antiderivatives
Fizza Rubab, Ntumba Elie Nsampi, Martin Balint +4
Neural fields offer continuous, learnable representations that extend beyond traditional discrete formats in visual computing. We study the problem of learning neural representatio…
Interactive Stroke-based Neural SDF Sculpting
Fizza Rubab, Yiying Tong
Recent advances in implicit neural representations have made them a popular choice for modeling 3D geometry. However, directly editing these representations presents challenges due…