activity
20182021
most citedIn the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations

1 citations · 2 across the 3 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Learning Speech-driven 3D Conversational Gestures from Video

Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta +5

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 vi…

cs.CV2021

Neural Re-Rendering of Humans from a Single Image

Kripasindhu Sarkar, Dushyant Mehta, Weipeng Xu +2

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, unrealisti…

cs.LG2020

Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces

Bert Moons, Parham Noorzad, Andrii Skliar +4

Current state-of-the-art Neural Architecture Search (NAS) methods neither efficiently scale to multiple hardware platforms, nor handle diverse architectural search-spaces. To remed…

cs.CV2019

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

Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller +7

We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions…

cs.LG20191 cited

Implicit Filter Sparsification In Convolutional Neural Networks

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 gradien…

cs.CV20191 cited

In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations

Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta +2

Convolutional Neural Network based approaches for monocular 3D human pose estimation usually require a large amount of training images with 3D pose annotations. While it is feasibl…