by America Ortiz | Dec 10, 2024 | Machine Learning
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models In this paper, we introduce LiteVAE, a new autoencoder design for LDMs, which leverages the 2D discrete wavelet transform to enhance scalability and computational efficiency over...
by America Ortiz | Dec 10, 2024 | Video Processing, Visual Computing
BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation We propose BetterDepth to achieve geometrically correct affine-invariant MDE while capturing fine details. Specifically, BetterDepth is a conditional diffusion-based refiner that...
by America Ortiz | Nov 24, 2024 | Rendering, Video Processing, Visual Computing
Revitalizing Legacy Video Content: Deinterlacing with Bidirectional Information Propagation In this paper, we present a deep-learning-based method for deinterlacing animated and live-action content. Our proposed method supports bidirectional spatio-temporal...
by America Ortiz | Nov 21, 2024 | Machine Learning
Factorized Motion Diffusion for Precise and Character-Agnostic Motion Inbetweening We propose a novel factorization of motion between a character-agnostic Bézier Motion Model (BMM), which can be trained on a large motion dataset, followed by a character-specific...
by America Ortiz | Nov 11, 2024 | Animation, Visual Computing
Skel-inbetweening for Intuitive Neural Motion Authoring In this paper, we introduce a Neural Motion Rig called SKEL-Betweener, tailored to interactive motion authoring. SKEL-Betweener is able to generate long motion sequences from two poses only, and enables...
