Search Results for author: Mihai Zanfir

Found 17 papers, 0 papers with code

PhoMoH: Implicit Photorealistic 3D Models of Human Heads

no code implementations14 Dec 2022 Mihai Zanfir, Thiemo Alldieck, Cristian Sminchisescu

We present PhoMoH, a neural network methodology to construct generative models of photo-realistic 3D geometry and appearance of human heads including hair, beards, an oral cavity, and clothing.

Structured 3D Features for Reconstructing Controllable Avatars

no code implementations13 Dec 2022 Enric Corona, Mihai Zanfir, Thiemo Alldieck, Eduard Gabriel Bazavan, Andrei Zanfir, Cristian Sminchisescu

We introduce Structured 3D Features, a model based on a novel implicit 3D representation that pools pixel-aligned image features onto dense 3D points sampled from a parametric, statistical human mesh surface.

3D Reconstruction Novel View Synthesis +1

BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation

no code implementations23 Jun 2022 Ivan Grishchenko, Valentin Bazarevsky, Andrei Zanfir, Eduard Gabriel Bazavan, Mihai Zanfir, Richard Yee, Karthik Raveendran, Matsvei Zhdanovich, Matthias Grundmann, Cristian Sminchisescu

We present BlazePose GHUM Holistic, a lightweight neural network pipeline for 3D human body landmarks and pose estimation, specifically tailored to real-time on-device inference.

3D Human Pose Estimation

Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothing

no code implementations CVPR 2022 Thiemo Alldieck, Mihai Zanfir, Cristian Sminchisescu

We present PHORHUM, a novel, end-to-end trainable, deep neural network methodology for photorealistic 3D human reconstruction given just a monocular RGB image.

3D Human Reconstruction 3D Reconstruction

HSPACE: Synthetic Parametric Humans Animated in Complex Environments

no code implementations23 Dec 2021 Eduard Gabriel Bazavan, Andrei Zanfir, Mihai Zanfir, William T. Freeman, Rahul Sukthankar, Cristian Sminchisescu

We combine a hundred diverse individuals of varying ages, gender, proportions, and ethnicity, with hundreds of motions and scenes, as well as parametric variations in body shape (for a total of 1, 600 different humans), in order to generate an initial dataset of over 1 million frames.

3D Human Pose Estimation Scene Understanding

AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training

no code implementations CVPR 2021 Mihai Fieraru, Mihai Zanfir, Silviu Cristian Pirlea, Vlad Olaru, Cristian Sminchisescu

AIFit is able to reconstruct 3d human pose and motion, reliably segment exercise repetitions, and identify in real-time the deviations between standards learnt from trainers, and the execution of a trainee.

Visual Grounding

Learning Complex 3D Human Self-Contact

no code implementations18 Dec 2020 Mihai Fieraru, Mihai Zanfir, Elisabeta Oneata, Alin-Ionut Popa, Vlad Olaru, Cristian Sminchisescu

Monocular estimation of three dimensional human self-contact is fundamental for detailed scene analysis including body language understanding and behaviour modeling.

3D Reconstruction

Human Synthesis and Scene Compositing

no code implementations23 Sep 2019 Mihai Zanfir, Elisabeta Oneata, Alin-Ionut Popa, Andrei Zanfir, Cristian Sminchisescu

Generating good quality and geometrically plausible synthetic images of humans with the ability to control appearance, pose and shape parameters, has become increasingly important for a variety of tasks ranging from photo editing, fashion virtual try-on, to special effects and image compression.

Image Compression Image Generation +1

Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images

no code implementations NeurIPS 2018 Andrei Zanfir, Elisabeta Marinoiu, Mihai Zanfir, Alin-Ionut Popa, Cristian Sminchisescu

The final stage of 3d pose and shape prediction is based on a learned attention process where information from different human body parts is optimally integrated.

Human Appearance Transfer

no code implementations CVPR 2018 Mihai Zanfir, Alin-Ionut Popa, Andrei Zanfir, Cristian Sminchisescu

We propose an automatic person-to-person appearance transfer model based on explicit parametric 3d human representations and learned, constrained deep translation network architectures for photographic image synthesis.

Image Generation

3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism

no code implementations CVPR 2018 Elisabeta Marinoiu, Mihai Zanfir, Vlad Olaru, Cristian Sminchisescu

We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism.

Emotion Recognition

Deep Multitask Architecture for Integrated 2D and 3D Human Sensing

no code implementations CVPR 2017 Alin-Ionut Popa, Mihai Zanfir, Cristian Sminchisescu

We propose a deep multitask architecture for \emph{fully automatic 2d and 3d human sensing} (DMHS), including \emph{recognition and reconstruction}, in \emph{monocular images}.

3D Human Pose Estimation

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