activity
20142023
most citedXNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

265 citations · 517 across the 24 of their papers we have counts for

collaborators

34 papers

cs.CV2023

AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatars

Mohit Mendiratta, Xingang Pan, Mohamed Elgharib +6

Capturing and editing full head performances enables the creation of virtual characters with various applications such as extended reality and media production. The past few years…

cs.CV2023★ 1 cited

GVP: Generative Volumetric Primitives

Mallikarjun B R, Xingang Pan, Mohamed Elgharib +1

Advances in 3D-aware generative models have pushed the boundary of image synthesis with explicit camera control. To achieve high-resolution image synthesis, several attempts have b…

cs.CV2023★ 2 cited

HQ3DAvatar: High Quality Controllable 3D Head Avatar

Kartik Teotia, Mallikarjun B R, Xingang Pan +4

Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynami…

cs.GR2023

LiveHand: Real-time and Photorealistic Neural Hand Rendering

Akshay Mundra, Mallikarjun B R, Jiayi Wang +3

The human hand is the main medium through which we interact with our surroundings, making its digitization an important problem. While there are several works modeling the geometry…

cs.CV2022★ 83 cited

An Implicit Parametric Morphable Dental Model

Congyi Zhang, Mohamed Elgharib, Gereon Fox +3

3D Morphable models of the human body capture variations among subjects and are useful in reconstruction and editing applications. Current dental models use an explicit mesh scene…

cs.GR2022

gCoRF: Generative Compositional Radiance Fields

Mallikarjun BR, Ayush Tewari, Xingang Pan +2

3D generative models of objects enable photorealistic image synthesis with 3D control. Existing methods model the scene as a global scene representation, ignoring the compositional…

cs.CV2022★ 2 cited

EventNeRF: Neural Radiance Fields from a Single Colour Event Camera

Viktor Rudnev, Mohamed Elgharib, Christian Theobalt +1

Asynchronously operating event cameras find many applications due to their high dynamic range, vanishingly low motion blur, low latency and low data bandwidth. The field saw remark…

cs.CV2022

ϕ-SfT: Shape-from-Template with a Physics-Based Deformation Model

Navami Kairanda, Edith Tretschk, Mohamed Elgharib +2

Shape-from-Template (SfT) methods estimate 3D surface deformations from a single monocular RGB camera while assuming a 3D state known in advance (a template). This is an important…

cs.CV2021

NeRF for Outdoor Scene Relighting

Viktor Rudnev, Mohamed Elgharib, William Smith +3

Photorealistic editing of outdoor scenes from photographs requires a profound understanding of the image formation process and an accurate estimation of the scene geometry, reflect…

cs.GR2021

Egocentric Videoconferencing

Mohamed Elgharib, Mohit Mendiratta, Justus Thies +5

We introduce a method for egocentric videoconferencing that enables hands-free video calls, for instance by people wearing smart glasses or other mixed-reality devices. Videoconfer…

cs.CV2021

Self-supervised Outdoor Scene Relighting

Ye Yu, Abhimitra Meka, Mohamed Elgharib +3

Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, req…

cs.CV2021★ 1 cited

StyleVideoGAN: A Temporal Generative Model using a Pretrained StyleGAN

Gereon Fox, Ayush Tewari, Mohamed Elgharib +1

Generative adversarial models (GANs) continue to produce advances in terms of the visual quality of still images, as well as the learning of temporal correlations. However, few wor…

cs.CV2021

Differentiable Event Stream Simulator for Non-Rigid 3D Tracking

Jalees Nehvi, Vladislav Golyanik, Franziska Mueller +3

This paper introduces the first differentiable simulator of event streams, i.e., streams of asynchronous brightness change signals recorded by event cameras. Our differentiable sim…

cs.CV2021★ 16 cited

PhotoApp: Photorealistic Appearance Editing of Head Portraits

Mallikarjun B R, Ayush Tewari, Abdallah Dib +8

Photorealistic editing of portraits is a challenging task as humans are very sensitive to inconsistencies in faces. We present an approach for high-quality intuitive editing of the…

cs.CV2021

Learning Speech-driven 3D Conversational Gestures from Video

Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta +5

We propose the first approach to automatically and jointly synthesize both the synchronous 3D conversational body and hand gestures, as well as 3D face and head animations, of a vi…

cs.CV2020

High-Fidelity Neural Human Motion Transfer from Monocular Video

Moritz Kappel, Vladislav Golyanik, Mohamed Elgharib +5

Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack…

cs.CV2020

EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream

Viktor Rudnev, Vladislav Golyanik, Jiayi Wang +4

3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using…

cs.CV2020★ 1 cited

i3DMM: Deep Implicit 3D Morphable Model of Human Heads

Tarun Yenamandra, Ayush Tewari, Florian Bernard +4

We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expr…

cs.CV2020

Learning Complete 3D Morphable Face Models from Images and Videos

Mallikarjun B R, Ayush Tewari, Hans-Peter Seidel +2

Most 3D face reconstruction methods rely on 3D morphable models, which disentangle the space of facial deformations into identity geometry, expressions and skin reflectance. These…

cs.CV2020★ 2 cited

PIE: Portrait Image Embedding for Semantic Control

Ayush Tewari, Mohamed Elgharib, Mallikarjun B R. +5

Editing of portrait images is a very popular and important research topic with a large variety of applications. For ease of use, control should be provided via a semantically meani…

cs.CV2020

User-assisted Video Reflection Removal

Amgad Ahmed, Suhong Kim, Mohamed Elgharib +1

Reflections in videos are obstructions that often occur when videos are taken behind reflective surfaces like glass. These reflections reduce the quality of such videos, lead to in…

cs.CV2020

Monocular Reconstruction of Neural Face Reflectance Fields

Mallikarjun B R., Ayush Tewari, Tae-Hyun Oh +7

The reflectance field of a face describes the reflectance properties responsible for complex lighting effects including diffuse, specular, inter-reflection and self shadowing. Most…

cs.CV2020

VideoForensicsHQ: Detecting High-quality Manipulated Face Videos

Gereon Fox, Wentao Liu, Hyeongwoo Kim +3

There are concerns that new approaches to the synthesis of high quality face videos may be misused to manipulate videos with malicious intent. The research community therefore deve…

cs.CV2020★ 6 cited

StyleRig: Rigging StyleGAN for 3D Control over Portrait Images

Ayush Tewari, Mohamed Elgharib, Gaurav Bharaj +5

StyleGAN generates photorealistic portrait images of faces with eyes, teeth, hair and context (neck, shoulders, background), but lacks a rig-like control over semantic face paramet…