96 citations · 131 across the 8 of their papers we have counts for
8 papers
FDLS: A Deep Learning Approach to Production Quality, Controllable, and Retargetable Facial Performances
Wan-Duo Kurt Ma, Muhammad Ghifary, J. P. Lewis +2
Visual effects commonly requires both the creation of realistic synthetic humans as well as retargeting actors' performances to humanoid characters such as aliens and monsters. Ach…
Exact Diffusion Inversion via Bi-directional Integration Approximation
Guoqiang Zhang, J. P. Lewis, W. Bastiaan Kleijn
Recently, various methods have been proposed to address the inconsistency issue of DDIM inversion to enable image editing, such as EDICT [36] and Null-text inversion [22]. However,…
Training-Free Neural Matte Extraction for Visual Effects
Sharif Elcott, J. P. Lewis, Nori Kanazawa +1
Alpha matting is widely used in video conferencing as well as in movies, television, and social media sites. Deep learning approaches to the matte extraction problem are well suite…
Directed Diffusion: Direct Control of Object Placement through Attention Guidance
Wan-Duo Kurt Ma, J. P. Lewis, Avisek Lahiri +2
Text-guided diffusion models such as DALLE-2, Imagen, eDiff-I, and Stable Diffusion are able to generate an effectively endless variety of images given only a short text prompt des…
NewsStories: Illustrating articles with visual summaries
Reuben Tan, Bryan A. Plummer, Kate Saenko +3
Recent self-supervised approaches have used large-scale image-text datasets to learn powerful representations that transfer to many tasks without finetuning. These methods often as…
NASA: Neural Articulated Shape Approximation
Boyang Deng, JP Lewis, Timothy Jeruzalski +4
Efficient representation of articulated objects such as human bodies is an important problem in computer vision and graphics. To efficiently simulate deformation, existing approach…
The HSIC Bottleneck: Deep Learning without Back-Propagation
Wan-Duo Kurt Ma, J. P. Lewis, W. Bastiaan Kleijn
We introduce the HSIC (Hilbert-Schmidt independence criterion) bottleneck for training deep neural networks. The HSIC bottleneck is an alternative to the conventional cross-entropy…
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary +3
A long-standing obstacle to progress in deep learning is the problem of vanishing and exploding gradients. Although, the problem has largely been overcome via carefully constructed…