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CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields

CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields

by America Ortiz | Mar 18, 2024 | Video Processing, Visual Computing

CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields In this paper, we introduce Controllable Artistic Radiance Fields (CoARF), a novel algorithm for controllable 3D scene stylization. CoARF enables style transfer for specified objects, compositional 3D...
Trajectory Augmentation for Robust Neural Locomotion Controllers

Trajectory Augmentation for Robust Neural Locomotion Controllers

by America Ortiz | Feb 5, 2024 | Animation, Visual Computing

Trajectory Augmentation for Robust Neural Locomotion Controllers In this work, we introduce Trajectory Augmentation (TrajAug), a fully automatic data augmentation technique that generates synthetic motion data by using motion matching to stitch sequences from the...
Stereo Conversion with Disparity-Aware Warping, Compositing and Inpainting

Stereo Conversion with Disparity-Aware Warping, Compositing and Inpainting

by America Ortiz | Jan 3, 2024 | Video Processing, Visual Computing

Stereo Conversion with Disparity-Aware Warping, Compositing and Inpainting In this paper, we present a novel method for high-resolution 2D-to-3D conversion. It is fully differentiable in all of its stages and performs disparity-informed warping, consistent...
Pose and Skeleton-aware Neural IK for Pose and Motion Editing

Pose and Skeleton-aware Neural IK for Pose and Motion Editing

by America Ortiz | Dec 11, 2023 | Animation, Visual Computing

Pose and Skeleton-aware Neural IK for Pose and Motion Editing In this work, we introduce SKEL-IK, a novel architecture and training scheme that is conditioned on a base pose and designed to flow information directly onto the skeletal graph structure, such that hard...
Empowering Convolutional Neural Networks with MetaSin Activation

Empowering Convolutional Neural Networks with MetaSin Activation

by America Ortiz | Dec 9, 2023 | Video Processing, Visual Computing

Empowering Convolutional Neural Networks with MetaSin Activation In this work, we propose replacing a baseline network’s existing activations with a novel ensemble function with trainable parameters. The proposed METASIN activation can be trained reliably without...
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