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03/30/2023
Few-shot Geometry-Aware Keypoint Localization
Supervised keypoint localization methods rely on large manually labeled ...
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03/10/2023
Neural Partial Differential Equations with Functional Convolution
We present a lightweighted neural PDE representation to discover the hid...
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05/21/2022
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Structured representations such as keypoints are widely used in pose tra...
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05/06/2022
LatentKeypointGAN: Controlling Images via Latent Keypoints – Extended Abstract
Generative adversarial networks (GANs) can now generate photo-realistic ...
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12/02/2021
GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
Segmenting an image into its parts is a frequent preprocess for high-lev...
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03/29/2021
LatentKeypointGAN: Controlling GANs via Latent Keypoints
Generative adversarial networks (GANs) have attained photo-realistic qua...
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10/23/2020
Nonseparable Symplectic Neural Networks
Predicting the behaviors of Hamiltonian systems has been drawing increas...
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08/18/2020
Soft Multicopter Control using Neural Dynamics Identification
Dynamic control of a soft-body robot to deliver complex behaviors with l...
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06/23/2020
Learning Physical Constraints with Neural Projections
We propose a new family of neural networks to predict the behaviors of p...
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06/07/2020
RoeNets: Predicting Discontinuity of Hyperbolic Systems from Continuous Data
We introduce Roe Neural Networks (RoeNets) that can predict the disconti...
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06/07/2020
Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamics
In the field of fluid numerical analysis, there has been a long-standing...
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05/11/2020
Symplectic Neural Networks in Taylor Series Form for Hamiltonian Systems
We propose an effective and light-weighted learning algorithm, Symplecti...
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02/01/2020