computer-vision-1

3D Face Animation

3260 papers • 126 benchmarks • 313 datasets

Image: Cudeiro et al

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in 3d-face-animation-4

Trend

Dataset

Best Model

Actions

Biwi 3D Audiovisual Corpus of Affective Communication - B3D(AC)^2

BEAT2

Libraries

i

Use these libraries to find 3d-face-animation-4 models and implementations

Datasets

PASCAL VOC

VOCASET

BEAT2

Biwi 3D Audiovisual Corpus of Affective Communication - B3D(AC)^2

Human Optical Flow

FEAFA+

Subtasks

No subtasks available.

Most implemented papers

Learning a model of facial shape and expression from 4D scans

Michael J. Black, J. Romero, Timo Bolkart, Tianye Li, Hao Li•Sun Nov 19 2017

Faces Learned with an Articulated Model and Expressions is low-dimensional but more expressive than the FaceWarehouse model and the Basel Face Model and is compared to these models by fitting them to static 3D scans and 4D sequences using the same optimization method.

1490

Content

VOCASET

0

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Learning an animatable detailed 3D face model from in-the-wild images

Michael J. Black, Timo Bolkart, Haiwen Feng, Yao Feng•Sun Dec 06 2020

This work presents the first approach that regresses 3D face shape and animatable details that are specific to an individual but change with expression, and introduces a novel detail-consistency loss that disentangles person-specific details from expression-dependent wrinkles.

735 0

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MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement

Yandong Wen, F. D. L. Torre, Alexander Richard, Yaser Sheikh, Michael Zollhoefer•Thu Apr 15 2021

A generic audio-driven facial animation approach that achieves highly realistic motion synthesis results for the entire face by disentangles audio-correlated and audio-uncorrelated information based on a novel cross-modality loss.

253 0

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Generating Holistic 3D Human Motion from Speech

Yandong Wen, Michael J. Black, Timo Bolkart, Hongwei Yi, Qiong Cao, Dacheng Tao, Hualin Liang, Yifei Liu•Wed Dec 07 2022

A novel speech-to-motion generation framework in which the face, body, and hands are modeled separately, and a cross-conditional autoregressive model that generates body poses and hand gestures, leading to coherent and realistic motions is proposed.

198 0

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EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

Xiangyu Zhu, Ziqiao Peng, Hao Wu, Zhenbo Song, Hao-Xuan Xu, Hongyan Liu, Jun He, Zhaoxin Fan•Sun Mar 19 2023

An end-to-end neural network to disentangle different emotions in speech so as to generate rich 3D facial expressions and outperforms state-of-the-art methods and exhibits more diverse facial movements.

172 0

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EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling

Haiyang Liu, You Zhou, Zihao Zhu, Giorgio Becherini, Yichen Peng, Mingyang Su, Xuefei Zhe, Naoya Iwamoto, Bo Zheng, Michael J. Black•Sat Dec 30 2023

Experiments demonstrate that EMAGE generates holistic gestures with state-of-the-art performance and is flexible in accepting predefined spatial-temporal gesture inputs, generating complete, audio-synchronized results.

79 0

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3D faces in motion: Fully automatic registration and statistical analysis

Timo Bolkart, Stefanie Wuhrer•Sat Jan 31 2015

This paper proposes an approach to robustly compute correspondences between a large set of facial motion sequences in a fully automatic way using a multilinear model as statistical prior and synthesizes new motion sequences and performs expression recognition.

30 0

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Capture, Learning, and Synthesis of 3D Speaking Styles

Michael J. Black, Timo Bolkart, Daniel Cudeiro, Cassidy Laidlaw, Anurag Ranjan•Tue May 07 2019

A unique 4D face dataset with about 29 minutes of 4D scans captured at 60 fps and synchronized audio from 12 speakers is introduced and VOCA (Voice Operated Character Animation) is learned, the only realistic 3D facial animation model that is readily applicable to unseen subjects without retargeting.

403 0

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Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose

H. Bao, Yong-Jin Liu, Ran Yi, Zipeng Ye, Juyong Zhang•Sun Feb 23 2020

A deep neural network model that takes an audio signal A of a source person and a very short video V of a target person as input, and outputs a synthesized high-quality talking face video with personalized head pose, making use of the visual information in V, expression and lip synchronization.

148 0

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FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning

Yifan Zhao, Chenxu Zhang, Yifei Huang, Ming Zeng, Saifeng Ni, M. Budagavi, Xiaohu Guo•Tue Aug 17 2021

Experimental results and user studies show the proposed talking face generation method can generate realistic talking face videos with not only synchronized lip motions, but also natural head movements and eye blinks, with better qualities than the results of state-of-the-art methods.

143 0

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