Search Results for author: Adrian Spurr

Found 10 papers, 6 papers with code

Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks

1 code implementation ICCV 2019 Zhe He, Adrian Spurr, Xucong Zhang, Otmar Hilliges

In this work, we present a novel method to alleviate this problem by leveraging generative adversarial training to synthesize an eye image conditioned on a target gaze direction.

Gaze Estimation gaze redirection

Cross-modal Deep Variational Hand Pose Estimation

1 code implementation CVPR 2018 Adrian Spurr, Jie Song, Seonwook Park, Otmar Hilliges

Furthermore, we show that our proposed method can be used without changes on depth images and performs comparably to specialized methods.

Hand Pose Estimation

PeCLR: Self-Supervised 3D Hand Pose Estimation from monocular RGB via Equivariant Contrastive Learning

1 code implementation ICCV 2021 Adrian Spurr, Aneesh Dahiya, Xi Wang, Xucong Zhang, Otmar Hilliges

Encouraged by the success of contrastive learning on image classification tasks, we propose a new self-supervised method for the structured regression task of 3D hand pose estimation.

3D Hand Pose Estimation Contrastive Learning +3

Guiding InfoGAN with Semi-Supervision

2 code implementations14 Jul 2017 Adrian Spurr, Emre Aksan, Otmar Hilliges

In this paper we propose a new semi-supervised GAN architecture (ss-InfoGAN) for image synthesis that leverages information from few labels (as little as 0. 22%, max.

Image Generation

Deep Pictorial Gaze Estimation

1 code implementation ECCV 2018 Seonwook Park, Adrian Spurr, Otmar Hilliges

In this paper, we introduce a novel deep neural network architecture specifically designed for the task of gaze estimation from single eye input.

Gaze Estimation

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 valid

A Skeleton-Driven Neural Occupancy Representation for Articulated Hands

no code implementations23 Sep 2021 Korrawe Karunratanakul, Adrian Spurr, Zicong Fan, Otmar Hilliges, Siyu Tang

We present Hand ArticuLated Occupancy (HALO), a novel representation of articulated hands that bridges the advantages of 3D keypoints and neural implicit surfaces and can be used in end-to-end trainable architectures.

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