165 citations · 293 across the 14 of their papers we have counts for
15 papers
Skeleton-to-Image Encoding: Enabling Skeleton Representation Learning via Vision-Pretrained Models
Siyuan Yang, Jun Liu, Hao Cheng +5
Recent advances in large-scale pretrained vision models have demonstrated impressive capabilities across a wide range of downstream tasks, including cross-modal and multi-modal sce…
Joint Models with Multiple Markers and Multiple Time-to-event Outcomes Using Variational Approximations
Benjamin Christoffersen, Keith Humphreys, Alessandro Gasparini +3
Joint models are well suited to modelling linked data from laboratories and health registers. However, there are few examples of joint models that allow for (a) multiple markers, (…
Decoding complexity: how machine learning is redefining scientific discovery
Ricardo Vinuesa, Paola Cinnella, Jean Rabault +10
As modern scientific instruments generate vast amounts of data and the volume of information in the scientific literature continues to grow, machine learning (ML) has become an ess…
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation
Marc Botet Colomer, Pier Luigi Dovesi, Theodoros Panagiotakopoulos +6
The goal of Online Domain Adaptation for semantic segmentation is to handle unforeseeable domain changes that occur during deployment, like sudden weather events. However, the high…
Learn the Time to Learn: Replay Scheduling in Continual Learning
Marcus Klasson, Hedvig Kjellström, Cheng Zhang
Replay methods are known to be successful at mitigating catastrophic forgetting in continual learning scenarios despite having limited access to historical data. However, storing h…
Going Deeper than Tracking: a Survey of Computer-Vision Based Recognition of Animal Pain and Affective States
Sofia Broomé, Marcelo Feighelstein, Anna Zamansky +6
Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go 'deeper' than tracking,…
Approximation Methods for Mixed Models with Probit Link Functions
Benjamin Christoffersen, Mark Clements, Hedvig Kjellström +1
We study approximation methods for a large class of mixed models with a probit link function that includes mixed versions of the binomial model, the multinomial model, and generali…
Multimodal analysis of the predictability of hand-gesture properties
Taras Kucherenko, Rajmund Nagy, Michael Neff +2
Embodied conversational agents benefit from being able to accompany their speech with gestures. Although many data-driven approaches to gesture generation have been proposed in rec…
Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech
Taras Kucherenko, Rajmund Nagy, Patrik Jonell +3
We propose a new framework for gesture generation, aiming to allow data-driven approaches to produce more semantically rich gestures. Our approach first predicts whether to gesture…
A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents
Rajmund Nagy, Taras Kucherenko, Birger Moell +3
Embodied conversational agents (ECAs) benefit from non-verbal behavior for natural and efficient interaction with users. Gesticulation - hand and arm movements accompanying speech…
How Do Fair Decisions Fare in Long-term Qualification?
Xueru Zhang, Ruibo Tu, Yang Liu +4
Although many fairness criteria have been proposed for decision making, their long-term impact on the well-being of a population remains unclear. In this work, we study the dynamic…
Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation
Taras Kucherenko, Dai Hasegawa, Naoshi Kaneko +2
This paper presents a novel framework for speech-driven gesture production, applicable to virtual agents to enhance human-computer interaction. Specifically, we extend recent deep-…
Bayesian nonparametric shared multi-sequence time series segmentation
Olga Mikheeva, Ieva Kazlauskaite, Hedvig Kjellström +1
In this paper, we introduce a method for segmenting time series data using tools from Bayesian nonparametrics. We consider the task of temporal segmentation of a set of time series…
Gesticulator: A framework for semantically-aware speech-driven gesture generation
Taras Kucherenko, Patrik Jonell, Sanne van Waveren +4
During speech, people spontaneously gesticulate, which plays a key role in conveying information. Similarly, realistic co-speech gestures are crucial to enable natural and smooth i…
A Neural Network Approach to Missing Marker Reconstruction in Human Motion Capture
Taras Kucherenko, Jonas Beskow, Hedvig Kjellström
Optical motion capture systems have become a widely used technology in various fields, such as augmented reality, robotics, movie production, etc. Such systems use a large number o…