24 citations · 73 across the 11 of their papers we have counts for
14 papers · 1 filter
SPHEAR: Spherical Head Registration for Complete Statistical 3D Modeling
Eduard Gabriel Bazavan, Andrei Zanfir, Thiemo Alldieck +3
We present \emph{SPHEAR}, an accurate, differentiable parametric statistical 3D human head model, enabled by a novel 3D registration method based on spherical embeddings. We shift…
Reconstructing Three-Dimensional Models of Interacting Humans
Mihai Fieraru, Mihai Zanfir, Elisabeta Oneata +3
Understanding 3d human interactions is fundamental for fine-grained scene analysis and behavioural modeling. However, most of the existing models predict incorrect, lifeless 3d est…
HUM3DIL: Semi-supervised Multi-modal 3D Human Pose Estimation for Autonomous Driving
Andrei Zanfir, Mihai Zanfir, Alexander Gorban +4
Autonomous driving is an exciting new industry, posing important research questions. Within the perception module, 3D human pose estimation is an emerging technology, which can ena…
PhoMoH: Implicit Photorealistic 3D Models of Human Heads
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,…
Structured 3D Features for Reconstructing Controllable Avatars
Enric Corona, Mihai Zanfir, Thiemo Alldieck +3
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, sta…
BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose Estimation
Ivan Grishchenko, Valentin Bazarevsky, Andrei Zanfir +7
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. B…
Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothing
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. Our pixel-aligned me…
HSPACE: Synthetic Parametric Humans Animated in Complex Environments
Eduard Gabriel Bazavan, Andrei Zanfir, Mihai Zanfir +3
Advances in the state of the art for 3d human sensing are currently limited by the lack of visual datasets with 3d ground truth, including multiple people, in motion, operating in…
THUNDR: Transformer-based 3D HUmaN Reconstruction with Markers
Mihai Zanfir, Andrei Zanfir, Eduard Gabriel Bazavan +3
We present THUNDR, a transformer-based deep neural network methodology to reconstruct the 3d pose and shape of people, given monocular RGB images. Key to our methodology is an inte…
Learning Complex 3D Human Self-Contact
Mihai Fieraru, Mihai Zanfir, Elisabeta Oneata +3
Monocular estimation of three dimensional human self-contact is fundamental for detailed scene analysis including body language understanding and behaviour modeling. Existing 3d re…
Neural Descent for Visual 3D Human Pose and Shape
Andrei Zanfir, Eduard Gabriel Bazavan, Mihai Zanfir +3
We present deep neural network methodology to reconstruct the 3d pose and shape of people, given an input RGB image. We rely on a recently introduced, expressivefull body statistic…
Human Synthesis and Scene Compositing
Mihai Zanfir, Elisabeta Oneata, Alin-Ionut Popa +2
Generating good quality and geometrically plausible synthetic images of humans with the ability to control appearance, pose and shape parameters, has become increasingly important…
Deep Multitask Architecture for Integrated 2D and 3D Human Sensing
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}. The…
Spatio-Temporal Attention Models for Grounded Video Captioning
Mihai Zanfir, Elisabeta Marinoiu, Cristian Sminchisescu
Automatic video captioning is challenging due to the complex interactions in dynamic real scenes. A comprehensive system would ultimately localize and track the objects, actions an…