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MagicFight: Personalized Martial Arts Combat Video Generation

Authors:

Jiancheng Huang,

Shifeng ChenAuthors Info & Claims

MM '24: Proceedings of the 32nd ACM International Conference on Multimedia

Pages 10833 - 10842

https://doi.org/10.1145/3664647.3680849

Published: 28 October 2024 Publication History

Abstract

Amid the surge in generic text-to-video generation, the field of personalized human video generation has witnessed notable advancements, primarily concentrated on single-person scenarios. However, to our knowledge, the domain of two-person interactions, particularly in the context of martial arts combat, remains uncharted. We identify a significant gap: existing models for single-person dancing generation prove insufficient for capturing the subtleties and complexities of two engaged fighters, resulting in challenges such as identity confusion, anomalous limbs, and action mismatches. To address this, we introduce a pioneering new task, Personalized Martial Arts Combat Video Generation. Our approach, MagicFight, is specifically crafted to overcome these hurdles. Given this pioneering task, we face a lack of appropriate datasets. Thus, we generate a bespoke dataset using the game physics engine Unity, meticulously crafting a multitude of 3D characters, martial arts moves, and scenes designed to represent the diversity of combat. MagicFight refines and adapts existing models and strategies to generate high-fidelity two-person combat videos that maintain individual identities and ensure seamless, coherent action sequences, thereby laying the groundwork for future innovations in the realm of interactive video content creation.

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Cited By

Liao ZPiao FHuang DLi XMa YFeng PFang HZeng LCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Freehand Sketch Generation from Mechanical ComponentsProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681046(6755-6764)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681046

Index Terms

MagicFight: Personalized Martial Arts Combat Video Generation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition

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cover image ACM Conferences

MM '24: Proceedings of the 32nd ACM International Conference on Multimedia

October 2024

11719 pages

ISBN:9798400706868

DOI:10.1145/3664647

General Chairs:
Jianfei Cai
Monash University, Australia
,
Mohan Kankanhalli
NUS, Singapore
,
Balakrishnan Prabhakaran
UT Dallas, USA
,
Susanne Boll
University of Oldenburg, Germany
,
Program Chairs:
Ramanathan Subramanian
University of Canberra & IIT Ropar, Australia
,
Liang Zheng
Australian National University, Australia
,
Vivek K. Singh
Rutgers University, USA
,
Pablo Cesar
Centrum Wiskunde & Informatica, Netherlands
,
Lexing Xie
Australian National University, Australia
,
Dong Xu
University of Hong Kong, Hong Kong

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Published: 28 October 2024

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MM '24: The 32nd ACM International Conference on Multimedia

October 28 - November 1, 2024

Melbourne VIC, Australia

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MM '24 Paper Acceptance Rate 1,150 of 4,385 submissions, 26%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Liao ZPiao FHuang DLi XMa YFeng PFang HZeng LCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Freehand Sketch Generation from Mechanical ComponentsProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681046(6755-6764)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681046

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