Search Results for author: Pavlo Molchanov

Found 35 papers, 10 papers with code

Global Context Vision Transformers

1 code implementation20 Jun 2022 Ali Hatamizadeh, Hongxu Yin, Jan Kautz, Pavlo Molchanov

We propose global context vision transformer (GC ViT), a novel architecture that enhances parameter and compute utilization.

Image Classification Inductive Bias +4

DRaCoN -- Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars

no code implementations29 Mar 2022 Amit Raj, Umar Iqbal, Koki Nagano, Sameh Khamis, Pavlo Molchanov, James Hays, Jan Kautz

In this work, we present, DRaCoN, a framework for learning full-body volumetric avatars which exploits the advantages of both the 2D and 3D neural rendering techniques.

Neural Rendering

GradViT: Gradient Inversion of Vision Transformers

no code implementations CVPR 2022 Ali Hatamizadeh, Hongxu Yin, Holger Roth, Wenqi Li, Jan Kautz, Daguang Xu, Pavlo Molchanov

In this work we demonstrate the vulnerability of vision transformers (ViTs) to gradient-based inversion attacks.

A-ViT: Adaptive Tokens for Efficient Vision Transformer

no code implementations CVPR 2022 Hongxu Yin, Arash Vahdat, Jose Alvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov

A-ViT achieves this by automatically reducing the number of tokens in vision transformers that are processed in the network as inference proceeds.

Image Classification

GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras

1 code implementation CVPR 2022 Ye Yuan, Umar Iqbal, Pavlo Molchanov, Kris Kitani, Jan Kautz

Since the joint reconstruction of human motions and camera poses is underconstrained, we propose a global trajectory predictor that generates global human trajectories based on local body movements.

3D Human Pose Estimation Human Mesh Recovery

When to Prune? A Policy towards Early Structural Pruning

no code implementations CVPR 2022 Maying Shen, Pavlo Molchanov, Hongxu Yin, Jose M. Alvarez

Through extensive experiments on ImageNet, we show that EPI empowers a quick tracking of early training epochs suitable for pruning, offering same efficacy as an otherwise ``oracle'' grid-search that scans through epochs and requires orders of magnitude more compute.

Network Pruning

HALP: Hardware-Aware Latency Pruning

no code implementations20 Oct 2021 Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez

We propose Hardware-Aware Latency Pruning (HALP) that formulates structural pruning as a global resource allocation optimization problem, aiming at maximizing the accuracy while constraining latency under a predefined budget.

NViT: Vision Transformer Compression and Parameter Redistribution

no code implementations10 Oct 2021 Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, Jan Kautz

On ImageNet-1K, we prune the DEIT-Base (Touvron et al., 2021) model to a 2. 6x FLOPs reduction, 5. 1x parameter reduction, and 1. 9x run-time speedup with only 0. 07% loss in accuracy.

Hardware-Aware Network Transformation

no code implementations29 Sep 2021 Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat

In the second phase, it solves the combinatorial selection of efficient operations using a novel constrained integer linear optimization approach.

Neural Architecture Search

Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion

no code implementations13 Jul 2021 Xin Dong, Hongxu Yin, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

Understanding the behavior and vulnerability of pre-trained deep neural networks (DNNs) can help to improve them.

LANA: Latency Aware Network Acceleration

no code implementations12 Jul 2021 Pavlo Molchanov, Jimmy Hall, Hongxu Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat

We analyze three popular network architectures: EfficientNetV1, EfficientNetV2 and ResNeST, and achieve accuracy improvement for all models (up to $3. 0\%$) when compressing larger models to the latency level of smaller models.

Neural Architecture Search Quantization

Optimal Quantization Using Scaled Codebook

no code implementations CVPR 2021 Yerlan Idelbayev, Pavlo Molchanov, Maying Shen, Hongxu Yin, Miguel A. Carreira-Perpinan, Jose M. Alvarez

We study the problem of quantizing N sorted, scalar datapoints with a fixed codebook containing K entries that are allowed to be rescaled.

Quantization

Adversarial Motion Modelling helps Semi-supervised Hand Pose Estimation

no code implementations10 Jun 2021 Adrian Spurr, Pavlo Molchanov, Umar Iqbal, Jan Kautz, Otmar Hilliges

Hand pose estimation is difficult due to different environmental conditions, object- and self-occlusion as well as diversity in hand shape and appearance.

Hand Pose Estimation

KAMA: 3D Keypoint Aware Body Mesh Articulation

no code implementations27 Apr 2021 Umar Iqbal, Kevin Xie, Yunrong Guo, Jan Kautz, Pavlo Molchanov

We present KAMA, a 3D Keypoint Aware Mesh Articulation approach that allows us to estimate a human body mesh from the positions of 3D body keypoints.

3D Human Pose Estimation 3D Human Shape Estimation +1

See through Gradients: Image Batch Recovery via GradInversion

2 code implementations CVPR 2021 Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

In this work, we introduce GradInversion, using which input images from a larger batch (8 - 48 images) can also be recovered for large networks such as ResNets (50 layers), on complex datasets such as ImageNet (1000 classes, 224x224 px).

Federated Learning Inference Attack +1

HarDNN: Feature Map Vulnerability Evaluation in CNNs

no code implementations22 Feb 2020 Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler

As Convolutional Neural Networks (CNNs) are increasingly being employed in safety-critical applications, it is important that they behave reliably in the face of hardware errors.

Decision Making

Importance Estimation for Neural Network Pruning

3 code implementations CVPR 2019 Pavlo Molchanov, Arun Mallya, Stephen Tyree, Iuri Frosio, Jan Kautz

On ResNet-101, we achieve a 40% FLOPS reduction by removing 30% of the parameters, with a loss of 0. 02% in the top-1 accuracy on ImageNet.

Network Pruning

Few-Shot Adaptive Gaze Estimation

1 code implementation ICCV 2019 Seonwook Park, Shalini De Mello, Pavlo Molchanov, Umar Iqbal, Otmar Hilliges, Jan Kautz

Inter-personal anatomical differences limit the accuracy of person-independent gaze estimation networks.

 Ranked #1 on Gaze Estimation on MPII Gaze (using extra training data)

Gaze Estimation Meta-Learning

SCOPS: Self-Supervised Co-Part Segmentation

1 code implementation CVPR 2019 Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, Jan Kautz

Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations.

Towards annotation-efficient segmentation via image-to-image translation

no code implementations2 Apr 2019 Eugene Vorontsov, Pavlo Molchanov, Christopher Beckham, Jan Kautz, Samuel Kadoury

Specifically, we propose a semi-supervised framework that employs unpaired image-to-image translation between two domains, presence vs. absence of cancer, as the unsupervised objective.

Brain Tumor Segmentation Image-to-Image Translation +2

Making Convolutional Networks Recurrent for Visual Sequence Learning

no code implementations CVPR 2018 Xiaodong Yang, Pavlo Molchanov, Jan Kautz

Recurrent neural networks (RNNs) have emerged as a powerful model for a broad range of machine learning problems that involve sequential data.

Action Recognition Face Alignment +3

Budget-Aware Activity Detection with A Recurrent Policy Network

no code implementations30 Nov 2017 Behrooz Mahasseni, Xiaodong Yang, Pavlo Molchanov, Jan Kautz

In this paper, we address the challenging problem of efficient temporal activity detection in untrimmed long videos.

Action Detection Activity Detection

Improving Landmark Localization with Semi-Supervised Learning

no code implementations CVPR 2018 Sina Honari, Pavlo Molchanov, Stephen Tyree, Pascal Vincent, Christopher Pal, Jan Kautz

First, we propose the framework of sequential multitasking and explore it here through an architecture for landmark localization where training with class labels acts as an auxiliary signal to guide the landmark localization on unlabeled data.

Small Data Image Classification

A Lightweight Approach for On-the-Fly Reflectance Estimation

no code implementations ICCV 2017 Kihwan Kim, Jinwei Gu, Stephen Tyree, Pavlo Molchanov, Matthias Nießner, Jan Kautz

In addition, we have created a large synthetic dataset, SynBRDF, which comprises a total of $500$K RGBD images rendered with a physically-based ray tracer under a variety of natural illumination, covering $5000$ materials and $5000$ shapes.

Color Constancy

Pruning Convolutional Neural Networks for Resource Efficient Inference

9 code implementations19 Nov 2016 Pavlo Molchanov, Stephen Tyree, Tero Karras, Timo Aila, Jan Kautz

We propose a new criterion based on Taylor expansion that approximates the change in the cost function induced by pruning network parameters.

Transfer Learning

Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network

no code implementations CVPR 2016 Pavlo Molchanov, Xiaodong Yang, Shalini Gupta, Kihwan Kim, Stephen Tyree, Jan Kautz

Automatic detection and classification of dynamic hand gestures in real-world systems intended for human computer interaction is challenging as: 1) there is a large diversity in how people perform gestures, making detection and classification difficult; 2) the system must work online in order to avoid noticeable lag between performing a gesture and its classification; in fact, a negative lag (classification before the gesture is finished) is desirable, as feedback to the user can then be truly instantaneous.

Classification General Classification +1

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