Search Results for author: Muhammed Kocabas

Found 18 papers, 12 papers with code

HMP: Hand Motion Priors for Pose and Shape Estimation from Video

no code implementations27 Dec 2023 Enes Duran, Muhammed Kocabas, Vasileios Choutas, Zicong Fan, Michael J. Black

Therefore, we develop a generative motion prior specific for hands, trained on the AMASS dataset which features diverse and high-quality hand motions.

3D Hand Pose Estimation Motion Estimation

HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video

1 code implementation30 Nov 2023 Zicong Fan, Maria Parelli, Maria Eleni Kadoglou, Muhammed Kocabas, Xu Chen, Michael J. Black, Otmar Hilliges

Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour.

3D Reconstruction Object +1

HUGS: Human Gaussian Splats

no code implementations29 Nov 2023 Muhammed Kocabas, Jen-Hao Rick Chang, James Gabriel, Oncel Tuzel, Anurag Ranjan

We achieve state-of-the-art rendering quality with a rendering speed of 60 FPS while being ~100x faster to train over previous work.

Neural Rendering Novel View Synthesis

PACE: Human and Camera Motion Estimation from in-the-wild Videos

no code implementations20 Oct 2023 Muhammed Kocabas, Ye Yuan, Pavlo Molchanov, Yunrong Guo, Michael J. Black, Otmar Hilliges, Jan Kautz, Umar Iqbal

This design combines the strengths of SLAM and motion priors, which leads to significant improvements in human and camera motion estimation.

Motion Estimation

Physically Plausible Full-Body Hand-Object Interaction Synthesis

no code implementations14 Sep 2023 Jona Braun, Sammy Christen, Muhammed Kocabas, Emre Aksan, Otmar Hilliges

Through a hierarchical framework, we first learn skill priors for both body and hand movements in a decoupled setting.

Human-Object Interaction Detection Object +1

Reconstructing Action-Conditioned Human-Object Interactions Using Commonsense Knowledge Priors

no code implementations6 Sep 2022 Xi Wang, Gen Li, Yen-Ling Kuo, Muhammed Kocabas, Emre Aksan, Otmar Hilliges

We further qualitatively evaluate the effectiveness of our method on real images and demonstrate its generalizability towards interaction types and object categories.

Human-Object Interaction Detection Object

TempCLR: Reconstructing Hands via Time-Coherent Contrastive Learning

1 code implementation1 Sep 2022 Andrea Ziani, Zicong Fan, Muhammed Kocabas, Sammy Christen, Otmar Hilliges

We introduce TempCLR, a new time-coherent contrastive learning approach for the structured regression task of 3D hand reconstruction.

Contrastive Learning Hand Pose 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

D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions

1 code implementation CVPR 2022 Sammy Christen, Muhammed Kocabas, Emre Aksan, Jemin Hwangbo, Jie Song, Otmar Hilliges

We introduce the dynamic grasp synthesis task: given an object with a known 6D pose and a grasp reference, our goal is to generate motions that move the object to a target 6D pose.

Motion Synthesis Object

Learning to Regress Bodies from Images using Differentiable Semantic Rendering

1 code implementation ICCV 2021 Sai Kumar Dwivedi, Nikos Athanasiou, Muhammed Kocabas, Michael J. Black

For Minimally-Clothed regions, we define the DSR-MC loss, which encourages a tight match between a rendered SMPL body and the minimally-clothed regions of the image.

Ranked #52 on 3D Human Pose Estimation on 3DPW (using extra training data)

3D human pose and shape estimation

PARE: Part Attention Regressor for 3D Human Body Estimation

1 code implementation ICCV 2021 Muhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges, Michael J. Black

Despite significant progress, we show that state of the art 3D human pose and shape estimation methods remain sensitive to partial occlusion and can produce dramatically wrong predictions although much of the body is observable.

3D human pose and shape estimation 3D Multi-Person Pose Estimation

Analytical Moment Regularizer for Training Robust Networks

no code implementations ICLR 2020 Modar Alfadly, Adel Bibi, Muhammed Kocabas, Bernard Ghanem

In this work, we propose a new training regularizer that aims to minimize the probabilistic expected training loss of a DNN subject to a generic Gaussian input.

Data Augmentation

MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network

4 code implementations ECCV 2018 Muhammed Kocabas, Salih Karagoz, Emre Akbas

In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.

Human Detection Keypoint Detection +1

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