Recently, deep equilibrium models (DEQs) have drawn increasing attention from the
machine learning community. However, DEQs are much less understood in terms of certified …

Diffusion models excel at producing high-quality samples but naively require hundreds of
iterations, prompting multiple attempts to distill the generation process into a faster network …

The field of animal affective computing is rapidly emerging, and analysis of facial
expressions is a crucial aspect. One of the most significant challenges that researchers in …

In this work, we introduce FaceXformer, an end-to-end unified transformer model for a
comprehensive range of facial analysis tasks such as face parsing, landmark detection …

Deep equilibrium models (DEQs), as a typical implicit neural network, have demonstrated
remarkable success on various tasks. There is, however, a lack of theoretical understanding …

Implicit-depth neural networks have grown as powerful alternatives to traditional networks in
various applications in recent years. However, these models often lack guarantees of …

Face alignment is a critical and difficult task for many facial analysis applications. Existing
VFA methods frequently ignore the consistency of facial geometries and textures across …

Implicit deep learning has recently gained popularity with applications ranging from meta-
learning to Deep Equilibrium Networks (DEQs). In its general formulation, it relies on …

Facial landmark detection, often termed as face alignment, is a well-studied research
problem in computer vision. Nonetheless, face alignment on asymmetrical expressions has …

Implicit neural networks (NNs) have demonstrated remarkable success in various tasks.
However, there is a lack of theoretical understanding of the connections and differences …