Media Summary: Authors: Galanakis, Efstathios*; Gecer, Baris; Lattas, Alexandros; Zafeiriou, Stefanos Description: Authors: Claudio Ferrari, Stefano Berretti, Alberto Del Bimbo Description: This tutorial focuses on the problem of reconstructing a ... Recent research work has developed powerful generative

3dmm Rf Convolutional Radiance Fields For 3d Face Modeling - Detailed Analysis & Overview

Authors: Galanakis, Efstathios*; Gecer, Baris; Lattas, Alexandros; Zafeiriou, Stefanos Description: Authors: Claudio Ferrari, Stefano Berretti, Alberto Del Bimbo Description: This tutorial focuses on the problem of reconstructing a ... Recent research work has developed powerful generative This work presents the state-of-the-art method for JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling We present a new method for multimodal conditional

The 3DI method applied on a video of Don Lemon, showing various pose and expression variations. The CUDA code of 3DI and ... While the problem of recovering the shape and diffuse albedo of a surface from images has been extensively studied, there is ... This inspiring antique device at the Deutsches Museum in Munich was originally used for converting photographs for print ... This was part of my talk at GTC Digital 2020 together with Yajie Zhao. I describe how we represent Authors: William A. P. Smith, Alassane Seck, Hannah Dee, Bernard Tiddeman, Joshua B. Tenenbaum, Bernhard Egger ... This is a recording of at keynote address I gave at 3DV 2025. In this talk, I will: 1) review recent work from our team on ...

This is a demo video for the release of Large Scale Given a single-view input image, the neural network regressor, predicts dense depth pixel values, and achieves

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3DMM-RF: Convolutional Radiance Fields for 3D Face Modeling
Welcome to CVPR2020 3D Face Modeling and Reconstruction Tutorial
MoRF: Morphable Radiance Fields for Multiview Neural Head Modeling
[3DV 2021] Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
Selfie to 3D Model - Computerphile
JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling
Multimodal Conditional 3D Face Geometry Generation
3DMM fitting example 1 (Don Lemon)
Recovering Facial Reflectance and Geometry from Multi-view Images
3D Face Reconstruction with Dense Landmarks
RigNeRF: Fully Controllable Neural 3D Portraits
[ICCV 2023] Relightify: Relightable 3D Faces from a Single Image via Diffusion Models
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3DMM-RF: Convolutional Radiance Fields for 3D Face Modeling

3DMM-RF: Convolutional Radiance Fields for 3D Face Modeling

Authors: Galanakis, Efstathios*; Gecer, Baris; Lattas, Alexandros; Zafeiriou, Stefanos Description:

Welcome to CVPR2020 3D Face Modeling and Reconstruction Tutorial

Welcome to CVPR2020 3D Face Modeling and Reconstruction Tutorial

Authors: Claudio Ferrari, Stefano Berretti, Alberto Del Bimbo Description: This tutorial focuses on the problem of reconstructing a ...

MoRF: Morphable Radiance Fields for Multiview Neural Head Modeling

MoRF: Morphable Radiance Fields for Multiview Neural Head Modeling

Recent research work has developed powerful generative

[3DV 2021] Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

[3DV 2021] Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

This work presents the state-of-the-art method for

Selfie to 3D Model - Computerphile

Selfie to 3D Model - Computerphile

Converting a single 2D photo into a

JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling

JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling

JNR: Joint-based Neural Rig Representation for Compact 3D Face Modeling

Multimodal Conditional 3D Face Geometry Generation

Multimodal Conditional 3D Face Geometry Generation

We present a new method for multimodal conditional

3DMM fitting example 1 (Don Lemon)

3DMM fitting example 1 (Don Lemon)

The 3DI method applied on a video of Don Lemon, showing various pose and expression variations. The CUDA code of 3DI and ...

Recovering Facial Reflectance and Geometry from Multi-view Images

Recovering Facial Reflectance and Geometry from Multi-view Images

While the problem of recovering the shape and diffuse albedo of a surface from images has been extensively studied, there is ...

3D Face Reconstruction with Dense Landmarks

3D Face Reconstruction with Dense Landmarks

Landmarks often play a key role in

RigNeRF: Fully Controllable Neural 3D Portraits

RigNeRF: Fully Controllable Neural 3D Portraits

... corresponding

[ICCV 2023] Relightify: Relightable 3D Faces from a Single Image via Diffusion Models

[ICCV 2023] Relightify: Relightable 3D Faces from a Single Image via Diffusion Models

Relightify: Relightable

Image Revolutions - A Neural Radiance Field 3d-reconstruction

Image Revolutions - A Neural Radiance Field 3d-reconstruction

This inspiring antique device at the Deutsches Museum in Munich was originally used for converting photographs for print ...

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

3D

What is a Linear 3D Morphable Face Model?

What is a Linear 3D Morphable Face Model?

This was part of my talk at GTC Digital 2020 together with Yajie Zhao. I describe how we represent

A Morphable Face Albedo Model

A Morphable Face Albedo Model

Authors: William A. P. Smith, Alassane Seck, Hannah Dee, Bernard Tiddeman, Joshua B. Tenenbaum, Bernhard Egger ...

Radiance Fields and the Future of Generative Media

Radiance Fields and the Future of Generative Media

This is a recording of at keynote address I gave at 3DV 2025. In this talk, I will: 1) review recent work from our team on ...

Large Scale Facial Model (LSFM) (Booth et al.)

Large Scale Facial Model (LSFM) (Booth et al.)

This is a demo video for the release of Large Scale

3D face depth and appearance reconstruction from single-view images using a deep regressor model

3D face depth and appearance reconstruction from single-view images using a deep regressor model

Given a single-view input image, the neural network regressor, predicts dense depth pixel values, and achieves