68 citations · 218 across the 63 of their papers we have counts for
4 papers · 1 filter
SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks
Shuja Khalid, Frank Rudzicz
This paper explores how graph neural networks (GNNs) can be used to enhance visual scene understanding and surgical skill assessment. By using GNNs to analyze the complex visual da…
RefiNeRF: Modelling dynamic neural radiance fields with inconsistent or missing camera parameters
Shuja Khalid, Frank Rudzicz
Novel view synthesis (NVS) is a challenging task in computer vision that involves synthesizing new views of a scene from a limited set of input images. Neural Radiance Fields (NeRF…
wildNeRF: Complete view synthesis of in-the-wild dynamic scenes captured using sparse monocular data
Shuja Khalid, Frank Rudzicz
We present a novel neural radiance model that is trainable in a self-supervised manner for novel-view synthesis of dynamic unstructured scenes. Our end-to-end trainable algorithm l…
DeepConsensus: using the consensus of features from multiple layers to attain robust image classification
Yuchen Li, Safwan Hossain, Kiarash Jamali +1
We consider a classifier whose test set is exposed to various perturbations that are not present in the training set. These test samples still contain enough features to map them t…