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...
by America Ortiz | Nov 4, 2024 | Animation, Visual Computing
RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards This paper presents a novel learning-based control framework that uses keyframing to incorporate high-level objectives in natural locomotion for legged robots....
by America Ortiz | Oct 1, 2024 | Video Processing, Visual Computing
Efficient Video Encoder Autotuning via Offline Bayesian Optimization and Supervised Learning We propose an efficient video encoder autotuner based on offline Bayesian optimization and supervised machine learning. Our proposal uses Bayesian optimization to search for a...
by America Ortiz | Sep 28, 2024 | Video Processing, Visual Computing
Lossy Image Compression with Foundation Diffusion Models In this work, we formulate the removal of quantization error as a denoising task, using diffusion to recover lost information in the transmitted image latent. September 28, 2024 European Conference on Computer...
