Search Results for author: Otmar Hilliges

Found 47 papers, 24 papers with code

Render In-between: Motion Guided Video Synthesis for Action Interpolation

no code implementations1 Nov 2021 Hsuan-I Ho, Xu Chen, Jie Song, Otmar Hilliges

We propose to address these issues in a motion-guided frame-upsampling framework that is capable of producing realistic human motion and appearance.

Motion Capture Neural Rendering

Shape-aware Multi-Person Pose Estimation from Multi-View Images

no code implementations ICCV 2021 Zijian Dong, Jie Song, Xu Chen, Chen Guo, Otmar Hilliges

In this paper we contribute a simple yet effective approach for estimating 3D poses of multiple people from multi-view images.

Multi-Person Pose Estimation

SPEC: Seeing People in the Wild with an Estimated Camera

1 code implementation ICCV 2021 Muhammed Kocabas, Chun-Hao P. Huang, Joachim Tesch, Lea Müller, Otmar Hilliges, Michael J. Black

We then train a novel network that concatenates the camera calibration to the image features and uses these together to regress 3D body shape and pose.

3D Multi-Person Pose Estimation

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.

Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation

no code implementations1 Jul 2021 Zicong Fan, Adrian Spurr, Muhammed Kocabas, Siyu Tang, Michael J. Black, Otmar Hilliges

In this paper we demonstrate that self-similarity, and the resulting ambiguities in assigning pixel observations to the respective hands and their parts, is a major cause of the final 3D pose error.

Hand Pose 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

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

PARE: Part Attention Regressor for 3D Human Body Estimation

1 code implementation ICCV 2021 Muhammed Kocabas, Chun-Hao P. Huang, Otmar Hilliges, Michael J. Black

Despite significant progress, we show that state of the art 3D human pose and shape estimation methods remain sensitive to partial occlusion and can produce dramatically wrong predictions although much of the body is observable.

3D Multi-Person Pose Estimation

VariTex: Variational Neural Face Textures

1 code implementation ICCV 2021 Marcel C. Bühler, Abhimitra Meka, Gengyan Li, Thabo Beeler, Otmar Hilliges

In this paper, we propose VariTex - to the best of our knowledge the first method that learns a variational latent feature space of neural face textures, which allows sampling of novel identities.

Face Model

SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes

1 code implementation ICCV 2021 Xu Chen, Yufeng Zheng, Michael J. Black, Otmar Hilliges, Andreas Geiger

However, this is problematic since the backward warp field is pose dependent and thus requires large amounts of data to learn.

Improved Learning of Robot Manipulation Tasks via Tactile Intrinsic Motivation

no code implementations22 Feb 2021 Nikola Vulin, Sammy Christen, Stefan Stevsic, Otmar Hilliges

In this paper we address the challenge of exploration in deep reinforcement learning for robotic manipulation tasks.

The Six Hug Commandments: Design and Evaluation of a Human-Sized Hugging Robot with Visual and Haptic Perception

no code implementations19 Jan 2021 Alexis E. Block, Sammy Christen, Roger Gassert, Otmar Hilliges, Katherine J. Kuchenbecker

We followed all six tenets to create a new robotic platform, HuggieBot 2. 0, that has a soft, warm, inflated body (HuggieChest) and uses visual and haptic sensing to deliver closed-loop hugging.


Spatial Attention Improves Iterative 6D Object Pose Estimation

no code implementations5 Jan 2021 Stefan Stevsic, Otmar Hilliges

Our main insight is that after the initial pose estimate, it is important to pay attention to distinct spatial features of the object in order to improve the estimation accuracy during alignment.

6D Pose Estimation 6D Pose Estimation using RGB

Self-Learning Transformations for Improving Gaze and Head Redirection

2 code implementations NeurIPS 2020 Yufeng Zheng, Seonwook Park, Xucong Zhang, Shalini De Mello, Otmar Hilliges

Furthermore, we show that in the presence of limited amounts of real-world training data, our method allows for improvements in the downstream task of semi-supervised cross-dataset gaze estimation.

Gaze Estimation

Convolutional Autoencoders for Human Motion Infilling

1 code implementation22 Oct 2020 Manuel Kaufmann, Emre Aksan, Jie Song, Fabrizio Pece, Remo Ziegler, Otmar Hilliges

At the heart of our approach lies the idea to cast motion infilling as an inpainting problem and to train a convolutional de-noising autoencoder on image-like representations of motion sequences.

Human Body Model Fitting by Learned Gradient Descent

no code implementations ECCV 2020 Jie Song, Xu Chen, Otmar Hilliges

We propose a novel algorithm for the fitting of 3D human shape to images.

Category Level Object Pose Estimation via Neural Analysis-by-Synthesis

no code implementations ECCV 2020 Xu Chen, Zijian Dong, Jie Song, Andreas Geiger, Otmar Hilliges

Many object pose estimation algorithms rely on the analysis-by-synthesis framework which requires explicit representations of individual object instances.

Image Generation Pose Estimation

Towards End-to-end Video-based Eye-Tracking

1 code implementation ECCV 2020 Seonwook Park, Emre Aksan, Xucong Zhang, Otmar Hilliges

Estimating eye-gaze from images alone is a challenging task, in large parts due to un-observable person-specific factors.

Eye Tracking

CoSE: Compositional Stroke Embeddings

1 code implementation NeurIPS 2020 Emre Aksan, Thomas Deselaers, Andrea Tagliasacchi, Otmar Hilliges

We demonstrate qualitatively and quantitatively that our proposed approach is able to model the appearance of individual strokes, as well as the compositional structure of larger diagram drawings.

A Spatio-temporal Transformer for 3D Human Motion Prediction

no code implementations18 Apr 2020 Emre Aksan, Peng Cao, Manuel Kaufmann, Otmar Hilliges

In this paper, we propose a novel Transformer-based architecture for the task of generative modelling of 3D human motion.

Human motion prediction motion prediction

The DIDI dataset: Digital Ink Diagram data

1 code implementation20 Feb 2020 Philippe Gervais, Thomas Deselaers, Emre Aksan, Otmar Hilliges

We are releasing a dataset of diagram drawings with dynamic drawing information.

Learning Functionally Decomposed Hierarchies for Continuous Control Tasks with Path Planning

no code implementations14 Feb 2020 Sammy Christen, Lukas Jendele, Emre Aksan, Otmar Hilliges

We present HiDe, a novel hierarchical reinforcement learning architecture that successfully solves long horizon control tasks and generalizes to unseen test scenarios.

Continuous Control Decision Making +1

Content-Consistent Generation of Realistic Eyes with Style

1 code implementation8 Nov 2019 Marcel Bühler, Seonwook Park, Shalini De Mello, Xucong Zhang, Otmar Hilliges

Accurately labeled real-world training data can be scarce, and hence recent works adapt, modify or generate images to boost target datasets.

Semantic Segmentation

Structured Prediction Helps 3D Human Motion Modelling

1 code implementation ICCV 2019 Emre Aksan, Manuel Kaufmann, Otmar Hilliges

This is implemented via a hierarchy of small-sized neural networks connected analogously to the kinematic chains in the human body as well as a joint-wise decomposition in the loss function.

Human motion prediction Motion Forecasting +2

Learning Functionally Decomposed Hierarchies for Continuous Navigation Tasks

no code implementations25 Sep 2019 Lukas Jendele, Sammy Christen, Emre Aksan, Otmar Hilliges

Hierarchical Reinforcement Learning (HRL) has held the promise to enhance the capabilities of RL agents via operation on different levels of temporal abstraction.

Continuous Control Decision Making +1

Sample Efficient Learning of Path Following and Obstacle Avoidance Behavior for Quadrotors

no code implementations28 Jun 2019 Stefan Stevsic, Tobias Naegeli, Javier Alonso-Mora, Otmar Hilliges

This enables an easy to implement learning algorithm that is robust to errors of the model used in the model predictive controller.

Imitation Learning

Demonstration-Guided Deep Reinforcement Learning of Control Policies for Dexterous Human-Robot Interaction

no code implementations27 Jun 2019 Sammy Christen, Stefan Stevsic, Otmar Hilliges

In this paper, we propose a method for training control policies for human-robot interactions such as handshakes or hand claps via Deep Reinforcement Learning.

Human robot interaction Motion Capture

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

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

STCN: Stochastic Temporal Convolutional Networks

1 code implementation ICLR 2019 Emre Aksan, Otmar Hilliges

Convolutional architectures have recently been shown to be competitive on many sequence modelling tasks when compared to the de-facto standard of recurrent neural networks (RNNs), while providing computational and modeling advantages due to inherent parallelism.

Unpaired Pose Guided Human Image Generation

1 code implementation8 Jan 2019 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 or type of outfit worn by the user.

Image-to-Image Translation Translation

Monocular Neural Image Based Rendering with Continuous View Control

2 code implementations ICCV 2019 Xu Chen, Jie Song, Otmar Hilliges

The approach is self-supervised and only requires 2D images and associated view transforms for training.

Novel View Synthesis

End-to-end Learning for Graph Decomposition

no code implementations ICCV 2019 Jie Song, Bjoern Andres, Michael Black, Otmar Hilliges, Siyu Tang

The new optimization problem can be viewed as a Conditional Random Field (CRF) in which the random variables are associated with the binary edge labels of the initial graph and the hard constraints are introduced in the CRF as high-order potentials.

Multi-Person Pose Estimation

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

Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings

2 code implementations12 May 2018 Seonwook Park, Xucong Zhang, Andreas Bulling, Otmar Hilliges

Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras.

Gaze Estimation

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

DeepWriting: Making Digital Ink Editable via Deep Generative Modeling

no code implementations25 Jan 2018 Emre Aksan, Fabrizio Pece, Otmar Hilliges

Digital ink promises to combine the flexibility and aesthetics of handwriting and the ability to process, search and edit digital text.

Style Transfer

Guiding InfoGAN with Semi-Supervision

1 code implementation14 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

Plan3D: Viewpoint and Trajectory Optimization for Aerial Multi-View Stereo Reconstruction

no code implementations25 May 2017 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.

Learning Human Motion Models for Long-term Predictions

no code implementations10 Apr 2017 Partha Ghosh, Jie Song, Emre Aksan, Otmar Hilliges

Furthermore, we propose new evaluation protocols to assess the quality of synthetic motion sequences even for which no ground truth data exists.

Motion Capture

Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos

no code implementations CVPR 2017 Jie Song, Li-Min Wang, Luc van Gool, Otmar Hilliges

Temporal information can provide additional cues about the location of body joints and help to alleviate these issues.

Pose Estimation

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