25 citations · 75 across the 32 of their papers we have counts for
36 papers
ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion
Jens Lundell, Alberta Longhini, Lei Shu +6
Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicken-and-egg problem: completin…
DLO-Splatting: Tracking Deformable Linear Objects Using 3D Gaussian Splatting
Holly Dinkel, Marcel Büsching, Alberta Longhini +5
This work presents DLO-Splatting, an algorithm for estimating the 3D shape of Deformable Linear Objects (DLOs) from multi-view RGB images and gripper state information through pred…
Cloth-Splatting: 3D Cloth State Estimation from RGB Supervision
Alberta Longhini, Marcel Büsching, Bardienus P. Duisterhof +4
We introduce Cloth-Splatting, a method for estimating 3D states of cloth from RGB images through a prediction-update framework. Cloth-Splatting leverages an action-conditioned dyna…
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks
Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco +3
Given a finite set of sample points, meta-learning algorithms aim to learn an optimal adaptation strategy for new, unseen tasks. Often, this data can be ambiguous as it might belon…
Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset
Xiaomeng Zhu, Talha Bilal, Pär Mårtensson +3
This paper is about effectively utilizing synthetic data for training deep neural networks for industrial parts classification, in particular, by taking into account the domain gap…
Will You Participate? Exploring the Potential of Robotics Competitions on Human-centric Topics
Yuchong Zhang, Miguel Vasco, Mårten Björkman +1
This paper presents findings from an exploratory needfinding study investigating the research current status and potential participation of the competitions on the robotics communi…
LM2D: Lyrics- and Music-Driven Dance Synthesis
Wenjie Yin, Xuejiao Zhao, Yi Yu +3
Dance typically involves professional choreography with complex movements that follow a musical rhythm and can also be influenced by lyrical content. The integration of lyrics in a…
Scalable Motion Style Transfer with Constrained Diffusion Generation
Wenjie Yin, Yi Yu, Hang Yin +2
Current training of motion style transfer systems relies on consistency losses across style domains to preserve contents, hindering its scalable application to a large number of do…
Component attention network for multimodal dance improvisation recognition
Jia Fu, Jiarui Tan, Wenjie Yin +2
Dance improvisation is an active research topic in the arts. Motion analysis of improvised dance can be challenging due to its unique dynamics. Data-driven dance motion analysis, i…
Music- and Lyrics-driven Dance Synthesis
Wenjie Yin, Qingyuan Yao, Yi Yu +3
Lyrics often convey information about the songs that are beyond the auditory dimension, enriching the semantic meaning of movements and musical themes. Such insights are important…
Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration
Parag Khanna, Elmira Yadollahi, Mårten Björkman +2
Despite significant improvements in robot capabilities, they are likely to fail in human-robot collaborative tasks due to high unpredictability in human environments and varying hu…
FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenes
Marcel Büsching, Josef Bengtson, David Nilsson +1
We introduce FlowIBR, a novel approach for efficient monocular novel view synthesis of dynamic scenes. Existing techniques already show impressive rendering quality but tend to foc…
Automated Construction of Time-Space Diagrams for Traffic Analysis Using Street-View Video Sequence
Tanay Rastogi, Mårten Björkman
Time-space diagrams are essential tools for analyzing traffic patterns and optimizing transportation infrastructure and traffic management strategies. Traditional data collection m…
TD-GEM: Text-Driven Garment Editing Mapper
Reza Dadfar, Sanaz Sabzevari, Mårten Björkman +1
Language-based fashion image editing allows users to try out variations of desired garments through provided text prompts. Inspired by research on manipulating latent representatio…
A Multimodal Data Set of Human Handovers with Design Implications for Human-Robot Handovers
Parag Khanna, Mårten Björkman, Christian Smith
Handovers are basic yet sophisticated motor tasks performed seamlessly by humans. They are among the most common activities in our daily lives and social environments. This makes m…
Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models
Wenjie Yin, Ruibo Tu, Hang Yin +3
Data-driven and controllable human motion synthesis and prediction are active research areas with various applications in interactive media and social robotics. Challenges remain i…
User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks
Parag Khanna, Elmira Yadollahi, Mårten Björkman +2
Despite great advances in what robots can do, they still experience failures in human-robot collaborative tasks due to high randomness in unstructured human environments. Moreover,…
Data-driven Grip Force Variation in Robot-Human Handovers
Parag Khanna, Mårten Björkman, Christian Smith
Handovers frequently occur in our social environments, making it imperative for a collaborative robotic system to master the skill of handover. In this work, we aim to investigate…
Dance Style Transfer with Cross-modal Transformer
Wenjie Yin, Hang Yin, Kim Baraka +2
We present CycleDance, a dance style transfer system to transform an existing motion clip in one dance style to a motion clip in another dance style while attempting to preserve mo…
On the Subspace Structure of Gradient-Based Meta-Learning
Gustaf Tegnér, Alfredo Reichlin, Hang Yin +2
In this work we provide an analysis of the distribution of the post-adaptation parameters of Gradient-Based Meta-Learning (GBML) methods. Previous work has noticed how, for the cas…
Bridging the gap between emotion and joint action
M. M. N. Bieńkiewicz, A. Smykovskyi, T. Olugbade +5
Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd.…
Monte Carlo Filtering Objectives: A New Family of Variational Objectives to Learn Generative Model and Neural Adaptive Proposal for Time Series
Shuangshuang Chen, Sihao Ding, Yiannis Karayiannidis +1
Learning generative models and inferring latent trajectories have shown to be challenging for time series due to the intractable marginal likelihoods of flexible generative models.…
Graph-based Normalizing Flow for Human Motion Generation and Reconstruction
Wenjie Yin, Hang Yin, Danica Kragic +1
Data-driven approaches for modeling human skeletal motion have found various applications in interactive media and social robotics. Challenges remain in these fields for generating…
Combining Planning and Learning of Behavior Trees for Robotic Assembly
Jonathan Styrud, Matteo Iovino, Mikael Norrlöf +2
Industrial robots can solve very complex tasks in controlled environments, but modern applications require robots able to operate in unpredictable surroundings as well. An increasi…