Search Results for author: Shih-En Wei

Found 10 papers, 5 papers with code

LiP-Flow: Learning Inference-time Priors for Codec Avatars via Normalizing Flows in Latent Space

no code implementations15 Mar 2022 Emre Aksan, Shugao Ma, Akin Caliskan, Stanislav Pidhorskyi, Alexander Richard, Shih-En Wei, Jason Saragih, Otmar Hilliges

To mitigate this asymmetry, we introduce a prior model that is conditioned on the runtime inputs and tie this prior space to the 3D face model via a normalizing flow in the latent space.

Face Model

Driving-Signal Aware Full-Body Avatars

no code implementations21 May 2021 Timur Bagautdinov, Chenglei Wu, Tomas Simon, Fabian Prada, Takaaki Shiratori, Shih-En Wei, Weipeng Xu, Yaser Sheikh, Jason Saragih

The core intuition behind our method is that better drivability and generalization can be achieved by disentangling the driving signals and remaining generative factors, which are not available during animation.

Imputation

Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality

no code implementations10 Apr 2021 Amin Jourabloo, Fernando de la Torre, Jason Saragih, Shih-En Wei, Te-Li Wang, Stephen Lombardi, Danielle Belko, Autumn Trimble, Hernan Badino

Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR).

SimPoE: Simulated Character Control for 3D Human Pose Estimation

no code implementations CVPR 2021 Ye Yuan, Shih-En Wei, Tomas Simon, Kris Kitani, Jason Saragih

Based on this refined kinematic pose, the policy learns to compute dynamics-based control (e. g., joint torques) of the character to advance the current-frame pose estimate to the pose estimate of the next frame.

3D Human Pose Estimation Frame

Supervision by Registration and Triangulation for Landmark Detection

1 code implementation25 Jan 2021 Xuanyi Dong, Yi Yang, Shih-En Wei, Xinshuo Weng, Yaser Sheikh, Shoou-I Yu

End-to-end training is made possible by differentiable registration and 3D triangulation modules.

Optical Flow Estimation

Image Disentanglement and Uncooperative Re-Entanglement for High-Fidelity Image-to-Image Translation

no code implementations11 Jan 2019 Adam W. Harley, Shih-En Wei, Jason Saragih, Katerina Fragkiadaki

Cross-domain image-to-image translation should satisfy two requirements: (1) preserve the information that is common to both domains, and (2) generate convincing images covering variations that appear in the target domain.

Disentanglement Image-to-Image Translation +1

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