Pavlo Molchanov

Pavlo Molchanov

Principal Research Scientist and Research Lead

NVIDIA Research

Biography

I am a principal research scientist and research lead with NVIDIA Research since 2015. My research is focused on efficient deep learning and human-centric computer vision in LPR team lead by Jan Kautz. In the area of network efficiency I am interested in methods for model acceleration, inversion, novel architectures and adaptive/conditional inference. In the area of human-centric vision I am working on face/body/hand landmarks and pose estimation, action/gesture recognition and designing novel human-computer interaction systems.

I obtained PhD from Tampere University of Technology, Finland in the area of signal processing in 2014 supervised by Karen Eguiazarian. My dissertation was focused on designing automatic target recognition systems for radars and general radar signal processing. During PhD studies I was honored to receive EuRAD best paper award in 2011 and EuRAD young engineer award in 2013. I received my master degree from National Aerospace University, Kharkiv, Ukraine in Radio Systems focusing on high-order spectrum techniques for signal processing and mentored by Alexander Totsky.

We always look for promising interns and full time positions, feel free to ping me for details. I am also interested in connecting with people who share similar research interests.

Publications

Full list with filter

Gradvit: Gradient inversion of vision transformers. Ali Hatamizadeh, Hongxu Yin, Holger Roth, Wenqi Li, Jan Kautz, Daguang Xu, Pavlo Molchanov (2022). In CVPR 2022.

PDF Cite Code CVPR2022

Do Gradient Inversion Attacks Make Federated Learning Unsafe?. Ali Hatamizadeh, Hongxu Yin, Pavlo Molchanov, Andriy Myronenko, Wenqi Li, Prerna Dogra, Andrew Feng, Mona G Flores, Jan Kautz, Daguang Xu, others (2022). arXiv preprint arXiv:2202.06924.

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DRaCoN--Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars. Amit Raj, Umar Iqbal, Koki Nagano, Sameh Khamis, Pavlo Molchanov, James Hays, Jan Kautz (2022). arXiv preprint arXiv:2203.15798.

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AViT: Adaptive Tokens for Efficient Vision Transformer. H. Yin, A. Vahdat, J. Alvarez, A. Mallya, J. Kautz, P. Molchanov (2021). In CVPR 2022.

PDF Cite Code CVPR2022 (Oral)

GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras. Ye Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani, Jan Kautz (2021). In CVPR 2022.

PDF Cite Code Project Video CVPR2022 (Oral)

When to Prune? A Policy towards Early Structural Pruning. Maying Shen, Pavlo Molchanov, Hongxu Yin, Jose M Alvarez (2021). In CVPR 2022.

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LANA: Latency Aware Network Acceleration. Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat (2021). In Arxiv.

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Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion. Xin Dong, Hongxu Yin, Jose M Alvarez, Jan Kautz, Pavlo Molchanov (2021). In XAI4CV 2022.

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Adversarial motion modelling helps semi-supervised hand pose estimation. Adrian Spurr, Pavlo Molchanov, Umar Iqbal, Jan Kautz, Otmar Hilliges (2021). arXiv preprint arXiv:2106.05954.

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DexYCB: A benchmark for capturing hand grasping of objects. Yu-Wei Chao, Wei Yang, Yu Xiang, Pavlo Molchanov, Ankur Handa, Jonathan Tremblay, Yashraj S Narang, Karl Van Wyk, Umar Iqbal, Stan Birchfield, others (2021). Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

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