44 citations · 83 across the 10 of their papers we have counts for
5 papers · 1 filter
HoloDiffusion: Training a 3D Diffusion Model using 2D Images
Animesh Karnewar, Andrea Vedaldi, David Novotny +1
Diffusion models have emerged as the best approach for generative modeling of 2D images. Part of their success is due to the possibility of training them on millions if not billion…
NeuForm: Adaptive Overfitting for Neural Shape Editing
Connor Z. Lin, Niloy J. Mitra, Gordon Wetzstein +2
Neural representations are popular for representing shapes, as they can be learned form sensor data and used for data cleanup, model completion, shape editing, and shape synthesis.…
ShapeFormer: Transformer-based Shape Completion via Sparse Representation
Xingguang Yan, Liqiang Lin, Niloy J. Mitra +3
We present ShapeFormer, a transformer-based network that produces a distribution of object completions, conditioned on incomplete, and possibly noisy, point clouds. The resultant d…
CLIP2StyleGAN: Unsupervised Extraction of StyleGAN Edit Directions
Rameen Abdal, Peihao Zhu, John Femiani +2
The success of StyleGAN has enabled unprecedented semantic editing capabilities, on both synthesized and real images. However, such editing operations are either trained with seman…
SmartAnnotator: An Interactive Tool for Annotating RGBD Indoor Images
Yu-Shiang Wong, Hung-Kuo Chu, Niloy J. Mitra
RGBD images with high quality annotations in the form of geometric (i.e., segmentation) and structural (i.e., how do the segments are mutually related in 3D) information provide va…