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Alibaba - Video Generation

LHM-1B

Alibaba's Large Animatable Human Reconstruction Model (LHM) is an innovative AI model that converts a single 2D image into a detailed 3D human avatar quickly. This advancement is significant for virtual reality, gaming, and e-commerce, offering lifelike and animatable avatars. LHM leverages a multimodal transformer and head feature pyramid encoding to capture intricate details like clothing and facial features, and it is trained on extensive video datasets for high efficiency and quality. Open-source and available on platforms like GitHub and Hugging Face, LHM outperforms competitors in speed and accuracy, making it a powerful tool for developers. Despite its strengths, LHM faces challenges with uncommon poses due to dataset biases. Future updates aim to improve its versatility. Users can explore and test the model through the provided online platforms.
2025-03-25
Updated 2025-03-25 08:12:23

Transform a Single Photo into a Lifelike 3D Avatar

Step into the future with Alibaba’s Large Animatable Human Reconstruction Model (LHM). Imagine the impossible made real: a single photograph blossoming into a stunning, animatable 3D avatar in mere seconds. This technological marvel is not just an evolution; it’s a revolution, destined to reshape virtual reality, gaming, and e-commerce landscapes.

Introducing LHM

Meet the pinnacle of AI innovation—LHM. This cutting-edge model crafts intricate 3D human avatars from just one 2D image. By harnessing a multimodal transformer and head feature pyramid encoding, it meticulously captures every detail, from the sway of a garment to the subtle nuances of a smile. Trained on vast video datasets, LHM delivers rapid results with unparalleled quality. And the best part? It's open-source, accessible on GitHub and Hugging Face under the Apache 2.0 license.

Why LHM Stands Unrivaled

In a world where speed and accuracy reign supreme, LHM is the undisputed champion. It boasts a Peak Signal-to-Noise Ratio (PSNR) of 25.183 on synthetic data, a figure that leaves competitors like AniGS trailing with 18.681. With lightning-fast inference times of just 2 seconds and efficient memory usage ranging from 18-24 GB, LHM is both formidable and efficient. Observe the comparison below:

Methods PSNR ↑ SSIM ↑ LPIPS ↓ FC ↓ Time ↓ Memory ↓
GTA 17.025 0.919 0.087 0.051 - -
SIFu 16.681 0.917 0.093 0.060 - -
PSHuman 17.556 0.921 0.076 0.037 - -
DreamGaussian 18.544 0.917 0.075 0.056 ~2 min -
En3D 15.231 0.734 0.172 0.058 5 min 32 GB
AniGS 18.681 0.871 0.103 0.053 15 min 24 GB
LHM-0.5B* 25.183 0.951 0.029 0.035 - -
LHM-0.5B + All 21.648 0.924 0.044 0.042 2.01s 18 GB
LHM-1B 22.003 0.930 0.040 0.035 6.57s 24 GB

Real-World Applications

  • VR & AR: Craft lifelike avatars for immersive experiences.
  • Gaming: Create detailed characters at the snap of a finger.
  • E-Commerce: Revolutionize sales with virtual try-ons.

What’s Next for LHM?

While LHM stands as a beacon of innovation, it is not without its challenges. Uncommon poses can prove tricky due to dataset biases. Yet, with continual updates, its versatility and prowess will only grow, securing its place as the ultimate tool for developers worldwide.

Experience LHM Today

Ready to be amazed? Dive into the LHM code on GitHub or explore it on Hugging Face. Alibaba’s LHM isn’t just a model—it’s the future of 3D reconstruction.

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