222 citations · 765 across the 21 of their papers we have counts for
16 papers · 1 filter
ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation
Xucong Zhang, Seonwook Park, Thabo Beeler +3
Gaze estimation is a fundamental task in many applications of computer vision, human computer interaction and robotics. Many state-of-the-art methods are trained and tested on cust…
Content-Consistent Generation of Realistic Eyes with Style
Marcel Bühler, Seonwook Park, Shalini De Mello +2
Accurately labeled real-world training data can be scarce, and hence recent works adapt, modify or generate images to boost target datasets. However, retaining relevant details fro…
Structured Prediction Helps 3D Human Motion Modelling
Emre Aksan, Manuel Kaufmann, Otmar Hilliges
Human motion prediction is a challenging and important task in many computer vision application domains. Existing work only implicitly models the spatial structure of the human ske…
Few-Shot Adaptive Gaze Estimation
Seonwook Park, Shalini De Mello, Pavlo Molchanov +3
Inter-personal anatomical differences limit the accuracy of person-independent gaze estimation networks. Yet there is a need to lower gaze errors further to enable applications req…
Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks
Zhe He, Adrian Spurr, Xucong Zhang +1
Gaze redirection is the task of changing the gaze to a desired direction for a given monocular eye patch image. Many applications such as videoconferencing, films, games, and gener…
Unpaired Pose Guided Human Image Generation
Xu Chen, Jie Song, Otmar Hilliges
This paper studies the task of full generative modelling of realistic images of humans, guided only by coarse sketch of the pose, while providing control over the specific instance…
Monocular Neural Image Based Rendering with Continuous View Control
Xu Chen, Jie Song, Otmar Hilliges
We present an approach that learns to synthesize high-quality, novel views of 3D objects or scenes, while providing fine-grained and precise control over the 6-DOF viewpoint. The a…
End-to-end Learning for Graph Decomposition
Jie Song, Bjoern Andres, Michael Black +2
We propose a novel end-to-end trainable framework for the graph decomposition problem. The minimum cost multicut problem is first converted to an unconstrained binary cubic formula…
Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility
Benjamin Hepp, Debadeepta Dey, Sudipta N. Sinha +3
Camera equipped drones are nowadays being used to explore large scenes and reconstruct detailed 3D maps. When free space in the scene is approximately known, an offline planner can…
Deep Pictorial Gaze Estimation
Seonwook Park, Adrian Spurr, Otmar Hilliges
Estimating human gaze from natural eye images only is a challenging task. Gaze direction can be defined by the pupil- and the eyeball center where the latter is unobservable in 2D…
Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings
Seonwook Park, Xucong Zhang, Andreas Bulling +1
Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras. In unconstrained re…
Cross-modal Deep Variational Hand Pose Estimation
Adrian Spurr, Jie Song, Seonwook Park +1
The human hand moves in complex and high-dimensional ways, making estimation of 3D hand pose configurations from images alone a challenging task. In this work we propose a method t…
Guiding InfoGAN with Semi-Supervision
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. 10% of the dat…
Plan3D: Viewpoint and Trajectory Optimization for Aerial Multi-View Stereo Reconstruction
Benjamin Hepp, Matthias Nießner, Otmar Hilliges
We introduce a new method that efficiently computes a set of viewpoints and trajectories for high-quality 3D reconstructions in outdoor environments. Our goal is to automatically e…
Learning Human Motion Models for Long-term Predictions
Partha Ghosh, Jie Song, Emre Aksan +1
We propose a new architecture for the learning of predictive spatio-temporal motion models from data alone. Our approach, dubbed the Dropout Autoencoder LSTM, is capable of synthes…
Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos
Jie Song, Limin Wang, Luc Van Gool +1
Deep ConvNets have been shown to be effective for the task of human pose estimation from single images. However, several challenging issues arise in the video-based case such as se…