ByteDance, the parent company of TikTok, has unveiled OmniHuman-1, a groundbreaking AI model capable of generating highly realistic full-body deepfake videos from just a single image and audio track. The technology represents a significant leap forward in deepfake capabilities, moving beyond previous models that could only animate faces or upper bodies.
Published in a research paper on Monday, OmniHuman-1 has quickly captured the attention of the AI research community. The model can generate realistic full-body animations that synchronize gestures and facial expressions with speech or music, creating remarkably lifelike results. ByteDance demonstrated the technology’s capabilities through several dozen test videos posted on its OmniHuman-lab project page, including AI-generated TED Talks and a talking Albert Einstein.
Matt Groh, an assistant professor at Northwestern University specializing in computational social science, emphasized the significance of this development, stating that “the realism of deepfakes just reached a whole new level with Bytedance’s release of OmniHuman-1.” The model was trained on approximately 19,000 hours of human motion data, enabling it to create video clips of any length within memory limits and adapt to different input signals.
What sets OmniHuman-1 apart is its support for different body proportions and aspect ratios, making the output appear more natural and realistic. According to ByteDance’s researchers, the model outperformed other animation tools in both realism and accuracy benchmarks, establishing a new standard for AI-generated video content.
This release follows the recent market-shaking debut of DeepSeek’s R1 model last month, marking another significant AI advancement from a Chinese tech company. Venky Balasubramanian, founder and CEO of tech company Plivo, noted the rapid pace of Chinese AI innovation, commenting that it seems like “another week another Chinese AI model.”
The advancement comes amid growing concerns about deepfake technology’s potential for misuse. As deepfakes become increasingly sophisticated and harder to detect, they’ve fueled harassment, fraud, and cyberattacks. Criminals have exploited AI-generated voices and videos to scam victims, prompting US regulators to issue alerts and lawmakers to introduce legislation specifically targeting deepfake pornography.
Tech giants including Google, Meta, and OpenAI have responded by introducing AI watermarking tools such as SynthID and Meta’s Video Seal to flag synthetic content. However, these detection tools are struggling to keep pace with the rapid advancement of deepfake technology. A recent World Economic Forum article highlighted how this technology is exposing critical security vulnerabilities across various sectors.
Key Quotes
The realism of deepfakes just reached a whole new level with Bytedance’s release of OmniHuman-1
Matt Groh, an assistant professor at Northwestern University specializing in computational social science, emphasized the unprecedented level of realism achieved by ByteDance’s new AI model, signaling a major advancement in deepfake technology that could have far-reaching implications for digital content authenticity.
Another week another Chinese AI model. OmniHuman-1 by Bytedance can create highly realistic human videos using only a single image and an audio track
Venky Balasubramanian, founder and CEO of tech company Plivo, highlighted the rapid pace of AI innovation coming from Chinese tech companies, noting how frequently groundbreaking models are being released and the minimal input requirements needed to generate sophisticated deepfake content.
Our Take
ByteDance’s OmniHuman-1 represents a watershed moment where deepfake technology transitions from a niche concern to a mainstream challenge. The model’s ability to generate full-body animations from minimal input—just one image and audio—dramatically lowers the barrier to creating convincing fake content. This democratization of sophisticated deepfake creation is a double-edged sword: while it could enable innovative applications in entertainment, education, and accessibility, it simultaneously amplifies risks of fraud, misinformation, and harassment.
What’s particularly concerning is the widening gap between creation and detection capabilities. Despite efforts by major tech companies to develop watermarking and detection tools, these safeguards are perpetually playing catch-up. The 19,000 hours of training data used for OmniHuman-1 demonstrates the scale of resources being invested in generation technology, while detection tools receive comparatively less attention. This asymmetry suggests we’re entering an era where visual evidence may lose its traditional evidentiary value, requiring fundamental shifts in how we verify authenticity and establish trust in digital spaces.
Why This Matters
OmniHuman-1’s release marks a critical inflection point in AI-generated content technology, demonstrating that full-body deepfake creation has become accessible and highly realistic. This development has profound implications for multiple sectors, from entertainment and education to security and misinformation.
The technology’s sophistication raises urgent questions about digital authenticity and trust in visual media. As deepfakes become indistinguishable from real footage, society faces challenges in verifying genuine content, which could impact everything from journalism and legal proceedings to personal privacy and corporate security.
The rapid succession of advanced AI models from Chinese tech companies—following DeepSeek’s R1 and now ByteDance’s OmniHuman-1—signals an intensifying global AI race. This competition is driving innovation at an unprecedented pace, but also creating regulatory challenges as governments struggle to establish frameworks for responsible AI use.
For businesses, this technology presents both opportunities and risks. While it could revolutionize content creation, marketing, and virtual communication, it also necessitates investment in deepfake detection systems and employee training to combat fraud. The gap between creation and detection capabilities creates a vulnerable window that bad actors can exploit, making this a critical concern for cybersecurity professionals and policymakers alike.
Recommended Reading
For those interested in learning more about artificial intelligence, machine learning, and effective AI communication, here are some excellent resources:
Recommended Reading
Related Stories
- Tech Tip: How to Spot AI-Generated Deepfake Images
- Jenna Ortega Speaks Out Against Explicit AI-Generated Images of Her
- Video game voice actors vote to allow use of AI voices
- Alien’s Ian Holm AI to Criticize Fans Without Family Permission in 2024
- The Disinformation Threat to Local Governments
Source: https://www.businessinsider.com/bytedance-omnihuman-ai-generated-deepfake-videos-2025-2