4 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…
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…