Search Results for author: Dimitrios Tzionas

Found 29 papers, 20 papers with code

POCO: 3D Pose and Shape Estimation with Confidence

no code implementations24 Aug 2023 Sai Kumar Dwivedi, Cordelia Schmid, Hongwei Yi, Michael J. Black, Dimitrios Tzionas

To address this, we develop POCO, a novel framework for training HPS regressors to estimate not only a 3D human body, but also their confidence, in a single feed-forward pass.

Action Recognition Pose Estimation +1

GRIP: Generating Interaction Poses Using Latent Consistency and Spatial Cues

no code implementations22 Aug 2023 Omid Taheri, Yi Zhou, Dimitrios Tzionas, Yang Zhou, Duygu Ceylan, Soren Pirk, Michael J. Black

In contrast, we introduce GRIP, a learning-based method that takes, as input, the 3D motion of the body and the object, and synthesizes realistic motion for both hands before, during, and after object interaction.

Mixed Reality Object

Reconstructing Signing Avatars From Video Using Linguistic Priors

no code implementations CVPR 2023 Maria-Paola Forte, Peter Kulits, Chun-Hao Huang, Vasileios Choutas, Dimitrios Tzionas, Katherine J. Kuchenbecker, Michael J. Black

A perceptual study shows that SGNify's 3D reconstructions are significantly more comprehensible and natural than those of previous methods and are on par with the source videos.

3D Human Pose Estimation via Intuitive Physics

no code implementations CVPR 2023 Shashank Tripathi, Lea Müller, Chun-Hao P. Huang, Omid Taheri, Michael J. Black, Dimitrios Tzionas

Inspired by biomechanics, we infer the pressure heatmap on the body, the Center of Pressure (CoP) from the heatmap, and the SMPL body's Center of Mass (CoM).

3D Human Pose Estimation

Detecting Human-Object Contact in Images

1 code implementation CVPR 2023 Yixin Chen, Sai Kumar Dwivedi, Michael J. Black, Dimitrios Tzionas

To build HOT, we use two data sources: (1) We use the PROX dataset of 3D human meshes moving in 3D scenes, and automatically annotate 2D image areas for contact via 3D mesh proximity and projection.

Object

ECON: Explicit Clothed humans Optimized via Normal integration

1 code implementation CVPR 2023 Yuliang Xiu, Jinlong Yang, Xu Cao, Dimitrios Tzionas, Michael J. Black

To increase robustness for these cases, existing work uses an explicit parametric body model to constrain surface reconstruction, but this limits the recovery of free-form surfaces such as loose clothing that deviates from the body.

Surface Reconstruction

SUPR: A Sparse Unified Part-Based Human Representation

1 code implementation25 Oct 2022 Ahmed A. A. Osman, Timo Bolkart, Dimitrios Tzionas, Michael J. Black

Using novel 4D scans of feet, we train a model with an extended kinematic tree that captures the range of motion of the toes.

InterCap: Joint Markerless 3D Tracking of Humans and Objects in Interaction

no code implementations26 Sep 2022 Yinghao Huang, Omid Tehari, Michael J. Black, Dimitrios Tzionas

With this method we capture the InterCap dataset, which contains 10 subjects (5 males and 5 females) interacting with 10 objects of various sizes and affordances, including contact with the hands or feet.

Object Pose Estimation

Accurate 3D Body Shape Regression using Metric and Semantic Attributes

1 code implementation CVPR 2022 Vasileios Choutas, Lea Muller, Chun-Hao P. Huang, Siyu Tang, Dimitrios Tzionas, Michael J. Black

Since paired data with images and 3D body shape are rare, we exploit two sources of information: (1) we collect internet images of diverse "fashion" models together with a small set of anthropometric measurements; (2) we collect linguistic shape attributes for a wide range of 3D body meshes and the model images.

3D Human Reconstruction 3D Human Shape Estimation

ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation

1 code implementation CVPR 2023 Zicong Fan, Omid Taheri, Dimitrios Tzionas, Muhammed Kocabas, Manuel Kaufmann, Michael J. Black, Otmar Hilliges

In part this is because there exist no datasets with ground-truth 3D annotations for the study of physically consistent and synchronised motion of hands and articulated objects.

3D Reconstruction Object

Human-Aware Object Placement for Visual Environment Reconstruction

1 code implementation CVPR 2022 Hongwei Yi, Chun-Hao P. Huang, Dimitrios Tzionas, Muhammed Kocabas, Mohamed Hassan, Siyu Tang, Justus Thies, Michael J. Black

In fact, we demonstrate that these human-scene interactions (HSIs) can be leveraged to improve the 3D reconstruction of a scene from a monocular RGB video.

3D Reconstruction Object

Embodied Hands: Modeling and Capturing Hands and Bodies Together

no code implementations7 Jan 2022 Javier Romero, Dimitrios Tzionas, Michael J. Black

We attach MANO to a standard parameterized 3D body shape model (SMPL), resulting in a fully articulated body and hand model (SMPL+H).

GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping

1 code implementation CVPR 2022 Omid Taheri, Vasileios Choutas, Michael J. Black, Dimitrios Tzionas

This is challenging, as it requires the avatar to walk towards the object with foot-ground contact, orient the head towards it, reach out, and grasp it with a realistic hand pose and hand-object contact.

Object

Populating 3D Scenes by Learning Human-Scene Interaction

1 code implementation CVPR 2021 Mohamed Hassan, Partha Ghosh, Joachim Tesch, Dimitrios Tzionas, Michael J. Black

Second, we show that POSA's learned representation of body-scene interaction supports monocular human pose estimation that is consistent with a 3D scene, improving on the state of the art.

Pose Estimation

GRAB: A Dataset of Whole-Body Human Grasping of Objects

2 code implementations ECCV 2020 Omid Taheri, Nima Ghorbani, Michael J. Black, Dimitrios Tzionas

Training computers to understand, model, and synthesize human grasping requires a rich dataset containing complex 3D object shapes, detailed contact information, hand pose and shape, and the 3D body motion over time.

Grasp Contact Prediction Grasp Generation +2

Learning Multi-Human Optical Flow

2 code implementations24 Oct 2019 Anurag Ranjan, David T. Hoffmann, Dimitrios Tzionas, Siyu Tang, Javier Romero, Michael J. Black

Therefore, we develop a dataset of multi-human optical flow and train optical flow networks on this dataset.

Optical Flow Estimation

Resolving 3D Human Pose Ambiguities with 3D Scene Constraints

1 code implementation ICCV 2019 Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, Michael J. Black

To motivate this, we show that current 3D human pose estimation methods produce results that are not consistent with the 3D scene.

3D Human Pose Estimation

Learning to Train with Synthetic Humans

2 code implementations2 Aug 2019 David T. Hoffmann, Dimitrios Tzionas, Micheal J. Black, Siyu Tang

Here we explore two variations of synthetic data for this challenging problem; a dataset with purely synthetic humans and a real dataset augmented with synthetic humans.

2D Pose Estimation Pose Estimation

Capturing Hand Motion with an RGB-D Sensor, Fusing a Generative Model with Salient Points

2 code implementations3 Apr 2017 Dimitrios Tzionas, Abhilash Srikantha, Pablo Aponte, Juergen Gall

In this work, we propose a framework for hand tracking that can capture the motion of two interacting hands using only a single, inexpensive RGB-D camera.

Pose Tracking

A Comparison of Directional Distances for Hand Pose Estimation

no code implementations3 Apr 2017 Dimitrios Tzionas, Juergen Gall

Benchmarking methods for 3d hand tracking is still an open problem due to the difficulty of acquiring ground truth data.

Benchmarking Hand Pose Estimation

Reconstructing Articulated Rigged Models from RGB-D Videos

no code implementations6 Sep 2016 Dimitrios Tzionas, Juergen Gall

Although commercial and open-source software exist to reconstruct a static object from a sequence recorded with an RGB-D sensor, there is a lack of tools that build rigged models of articulated objects that deform realistically and can be used for tracking or animation.

Clustering Motion Segmentation +1

Capturing Hands in Action using Discriminative Salient Points and Physics Simulation

2 code implementations6 Jun 2015 Dimitrios Tzionas, Luca Ballan, Abhilash Srikantha, Pablo Aponte, Marc Pollefeys, Juergen Gall

Hand motion capture is a popular research field, recently gaining more attention due to the ubiquity of RGB-D sensors.

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