no code implementations • 21 Aug 2023 • Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen, Danhang Tang, Thabo Beeler, Mingsong Dou, yinda zhang, Sasa Petrovic, Hyung Jin Chang, Jonathan Taylor, Bardia Doosti
We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images.
We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner.
no code implementations • • Ziqian Bai, Feitong Tan, Zeng Huang, Kripasindhu Sarkar, Danhang Tang, Di Qiu, Abhimitra Meka, Ruofei Du, Mingsong Dou, Sergio Orts-Escolano, Rohit Pandey, Ping Tan, Thabo Beeler, Sean Fanello, yinda zhang
The learnt avatar is driven by a parametric face model to achieve user-controlled facial expressions and head poses.
Furthermore, inspired by the compositional nature of interactions that humans can simultaneously interact with multiple objects, we define interaction semantics as the composition of varying numbers of atomic action-object pairs.
The challenge of synthesizing eyes is multifold as it requires 1) appropriate representations for the various components of the eye and the periocular region for coherent viewpoint synthesis, capable of representing diffuse, refractive and highly reflective surfaces, 2) disentangling skin and eye appearance from environmental illumination such that it may be rendered under novel lighting conditions, and 3) capturing eyeball motion and the deformation of the surrounding skin to enable re-gazing.
In this paper, we propose VariTex - to the best of our knowledge the first method that learns a variational latent feature space of neural face textures, which allows sampling of novel identities.
Recent monocular human performance capture approaches have shown compelling dense tracking results of the full body from a single RGB camera.
We show that our dataset can significantly improve the robustness of gaze estimation methods across different head poses and gaze angles.
Ranked #1 on Gaze Estimation on ETH-XGaze (using extra training data)
We present a style-preserving visual dubbing approach from single video inputs, which maintains the signature style of target actors when modifying facial expressions, including mouth motions, to match foreign languages.
1 code implementation • 3 Sep 2019 • Bernhard Egger, William A. P. Smith, Ayush Tewari, Stefanie Wuhrer, Michael Zollhoefer, Thabo Beeler, Florian Bernard, Timo Bolkart, Adam Kortylewski, Sami Romdhani, Christian Theobalt, Volker Blanz, Thomas Vetter
In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed.
Calibrating the intrinsic properties of a camera is one of the fundamental tasks required for a variety of computer vision and image processing tasks.
We present a method to continuously blend between multiple facial performances of an actor, which can contain different facial expressions or emotional states.