activity
20222026
most citedA Comprehensive Review of Data-Driven Co-Speech Gesture Generation

99 citations · 215 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

The GENEA Challenge 2026: A Large-Scale Disentangled Evaluation of Speech-Driven Gesture Generation on the Seamless Interaction Dataset

Rajmund Nagy, Silvia Arellano García, Hendric Voss +4

This preprint presents the results of the fourth GENEA Challenge, a large-scale human evaluation of five speech-driven gesture-generation systems trained by participating teams on…

cs.GR2026

StayStill: a large-scale 3D idle animation dataset

Eneko Atxa Landa, Igor Rodriguez, Elena Lazkano +1

Idle animations are essential for virtual characters, as they convey realistic behaviour during inactive states. While automatic animation generation has been widely studied, limit…

cs.CV2025

Towards Reliable Human Evaluations in Gesture Generation: Insights from a Community-Driven State-of-the-Art Benchmark

Rajmund Nagy, Hendric Voss, Thanh Hoang-Minh +18

We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed experimental setups. This leads…

cs.HC2024★ 2 cited

Towards a GENEA Leaderboard -- an Extended, Living Benchmark for Evaluating and Advancing Conversational Motion Synthesis

Rajmund Nagy, Hendric Voss, Youngwoo Yoon +7

Current evaluation practices in speech-driven gesture generation lack standardisation and focus on aspects that are easy to measure over aspects that actually matter. This leads to…

cs.CV2024★ 1 cited

Evaluating the Evaluators: Towards Human-aligned Metrics for Missing Markers Reconstruction

Taras Kucherenko, Derek Peristy, Judith Bütepage

Animation data is often obtained through optical motion capture systems, which utilize a multitude of cameras to establish the position of optical markers. However, system errors o…

cs.HC2023

The GENEA Challenge 2023: A large scale evaluation of gesture generation models in monadic and dyadic settings

Taras Kucherenko, Rajmund Nagy, Youngwoo Yoon +4

This paper reports on the GENEA Challenge 2023, in which participating teams built speech-driven gesture-generation systems using the same speech and motion dataset, followed by a…

cs.HC2023★ 26 cited

Evaluating gesture generation in a large-scale open challenge: The GENEA Challenge 2022

Taras Kucherenko, Pieter Wolfert, Youngwoo Yoon +4

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to bui…

cs.GR2023★ 99 cited

A Comprehensive Review of Data-Driven Co-Speech Gesture Generation

Simbarashe Nyatsanga, Taras Kucherenko, Chaitanya Ahuja +2

Gestures that accompany speech are an essential part of natural and efficient embodied human communication. The automatic generation of such co-speech gestures is a long-standing p…

cs.HC2022★ 87 cited

The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation

Youngwoo Yoon, Pieter Wolfert, Taras Kucherenko +4

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to bui…