Explore 3 peer-reviewed studies by C Hu in Motion Customization of Text-to-Video Diffusion Models and Crowdwork Fairness (2023–2025). Discover research powered by Prolific's participant panel.
This page lists 3 peer-reviewed papers authored or co-authored by C Hu in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: Y Wu, C Huang, F Yang, F Wang
Year: 2025
Published in: ArXiv
Institution: Nvidia, National Taiwan University
Research Area: Motion Customization of Text-to-Video Diffusion Models
Discipline: Computer Vision, Pattern Recognition
MotionMatcher is a novel framework for motion customization in text-to-video (T2V) diffusion models, using high-level spatio-temporal motion features rather than pixel-level objectives, achieving state-of-the-art performance.
Methods: Fine-tuning pre-trained text-to-video diffusion models at feature level by comparing spatio-temporal motion features instead of pixel-level objectives to address motion customization from reference videos.
Key Findings: Efficacy of motion customization in T2V models; ability to accurately capture complex motion and avoid content leakage from reference videos.
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Authors: M Gonzalez-Cabello, A Siddiq, CJ Corbett, C Hu
Year: 2024
Published in: Business Horizons, 2024 - Elsevier
Research Area: Crowdwork Fairness, Human-AI Supply Chain, Business Ethics, Management
Discipline: Business Ethics, Management
DOI: https://doi.org/10.1016/j.bushor.2024.09.003
Citations: 7
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Authors: C Huber, A Dreber, J Huber, M Johannesson
Year: 2023
Published in: Proceedings of the ..., 2023 - pnas.org
Institution: Aalto University School of Business, Stockholm School of Economics, Stockholm University, University of Innsbruck
Research Area: Moral Behavior, Competition, Behavioral Science, Meta-analysis of Experimental Designs
Discipline: Behavioral Science
Citations: 59