Search Results for author: Dushyant Mehta

Found 15 papers, 3 papers with code

Learning Speech-driven 3D Conversational Gestures from Video

no code implementations13 Feb 2021 Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Lingjie Liu, Hans-Peter Seidel, Gerard Pons-Moll, Mohamed Elgharib, Christian Theobalt

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 virtual character from speech input.

Hand Pose Estimation

Neural Re-Rendering of Humans from a Single Image

no code implementations ECCV 2020 Kripasindhu Sarkar, Dushyant Mehta, Weipeng Xu, Vladislav Golyanik, Christian Theobalt

Human re-rendering from a single image is a starkly under-constrained problem, and state-of-the-art algorithms often exhibit undesired artefacts, such as over-smoothing, unrealistic distortions of the body parts and garments, or implausible changes of the texture.

Translation

Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces

no code implementations ICCV 2021 Bert Moons, Parham Noorzad, Andrii Skliar, Giovanni Mariani, Dushyant Mehta, Chris Lott, Tijmen Blankevoort

Second, a rapid evolutionary search finds a set of pareto-optimal architectures for any scenario using the accuracy predictor and on-device measurements.

Knowledge Distillation Model Compression +1

XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera

4 code implementations1 Jul 2019 Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller, Weipeng Xu, Mohamed Elgharib, Pascal Fua, Hans-Peter Seidel, Helge Rhodin, Gerard Pons-Moll, Christian Theobalt

The first stage is a convolutional neural network (CNN) that estimates 2D and 3D pose features along with identity assignments for all visible joints of all individuals. We contribute a new architecture for this CNN, called SelecSLS Net, that uses novel selective long and short range skip connections to improve the information flow allowing for a drastically faster network without compromising accuracy.

Monocular 3D Human Pose Estimation

Emergence of Implicit Filter Sparsity in Convolutional Neural Networks

no code implementations ICML Workshop Deep_Phenomen 2019 Dushyant Mehta, Kwang In Kim, Christian Theobalt

We show implicit filter level sparsity manifests in convolutional neural networks (CNNs) which employ Batch Normalization and ReLU activation, and are trained using adaptive gradient descent techniques with L2 regularization or weight decay.

L2 Regularization

Implicit Filter Sparsification In Convolutional Neural Networks

no code implementations13 May 2019 Dushyant Mehta, Kwang In Kim, Christian Theobalt

We show implicit filter level sparsity manifests in convolutional neural networks (CNNs) which employ Batch Normalization and ReLU activation, and are trained with adaptive gradient descent techniques and L2 regularization or weight decay.

L2 Regularization

On Implicit Filter Level Sparsity in Convolutional Neural Networks

no code implementations CVPR 2019 Dushyant Mehta, Kwang In Kim, Christian Theobalt

We investigate filter level sparsity that emerges in convolutional neural networks (CNNs) which employ Batch Normalization and ReLU activation, and are trained with adaptive gradient descent techniques and L2 regularization or weight decay.

L2 Regularization

Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB

6 code implementations9 Dec 2017 Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller, Weipeng Xu, Srinath Sridhar, Gerard Pons-Moll, Christian Theobalt

Our approach uses novel occlusion-robust pose-maps (ORPM) which enable full body pose inference even under strong partial occlusions by other people and objects in the scene.

3D Pose Estimation

MonoPerfCap: Human Performance Capture from Monocular Video

no code implementations7 Aug 2017 Weipeng Xu, Avishek Chatterjee, Michael Zollhöfer, Helge Rhodin, Dushyant Mehta, Hans-Peter Seidel, Christian Theobalt

Reconstruction from monocular video alone is drastically more challenging, since strong occlusions and the inherent depth ambiguity lead to a highly ill-posed reconstruction problem.

Pose Estimation

VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera

1 code implementation3 May 2017 Dushyant Mehta, Srinath Sridhar, Oleksandr Sotnychenko, Helge Rhodin, Mohammad Shafiei, Hans-Peter Seidel, Weipeng Xu, Dan Casas, Christian Theobalt

A real-time kinematic skeleton fitting method uses the CNN output to yield temporally stable 3D global pose reconstructions on the basis of a coherent kinematic skeleton.

3D Human Pose Estimation

Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision

no code implementations29 Nov 2016 Dushyant Mehta, Helge Rhodin, Dan Casas, Pascal Fua, Oleksandr Sotnychenko, Weipeng Xu, Christian Theobalt

We propose a CNN-based approach for 3D human body pose estimation from single RGB images that addresses the issue of limited generalizability of models trained solely on the starkly limited publicly available 3D pose data.

Monocular 3D Human Pose Estimation Transfer Learning

Deep Shading: Convolutional Neural Networks for Screen-Space Shading

no code implementations19 Mar 2016 Oliver Nalbach, Elena Arabadzhiyska, Dushyant Mehta, Hans-Peter Seidel, Tobias Ritschel

In computer vision, convolutional neural networks (CNNs) have recently achieved new levels of performance for several inverse problems where RGB pixel appearance is mapped to attributes such as positions, normals or reflectance.

Image Generation

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