Hunyuan-GameCraft
Hunyuan-GameCraft is a research-grade diffusion-based framework for high-dynamic, controllable interactive game video generation that unifies keyboard and mouse inputs into a continuous camera representation and uses hybrid history-conditioned training to produce long, consistent gameplay videos.
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Quick Overview
Best for: Software & Gaming
What it does
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Best fit
Software & Gaming
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Hunyuan-GameCraft
Hunyuan-GameCraft is a diffusion-based framework designed to generate high-dynamic, temporally coherent interactive gameplay videos. It unifies standard keyboard and mouse inputs into a shared continuous camera representation, encodes actions with a light-weight action encoder, and uses a hybrid history-conditioned training strategy to autoregressively extend video sequences while preserving scene information. The framework incorporates model distillation to improve inference efficiency and is trained on a large-scale dataset of over one million gameplay recordings across more than 100 AAA games, then fine-tuned on annotated synthetic data to improve precision and control.
An open-source model by Tencent that generates playable, high-dynamic game videos from a single image and user actions, offering fine-grained control and impressive realism.
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Claim this listing for $29Key Features
Unified input representation
Standard keyboard and mouse inputs are transformed into a shared continuous camera representation space to enable smooth interpolation between camera and movement operations.
Light-weight action encoder
A compact action encoder encodes input camera trajectories and adds action and image features after patchify for conditioned generation.
Hybrid history-conditioned training
A hybrid history-conditioned strategy extends video sequences autoregressively and preserves game scene information using a variable mask indicator for history and predicted frames.
Model distillation for efficiency
Model distillation reduces computational overhead while maintaining long-term temporal consistency and playability for real-time deployment.
Large-scale game dataset
Trained on over one million gameplay recordings spanning 100+ AAA games and fine-tuned on an annotated synthetic dataset to enhance visual fidelity and control precision.
Pricing
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Use Cases
Interactive gameplay video generation
Generate controllable, temporally coherent gameplay videos from reference images, prompts, and input action signals for interactive experiences.
Third-person and first-person game scenarios
Generalizes to both third-person and first-person perspectives for a variety of game genres and camera setups.
Trajectory exploration and visualization
Explore and visualize multiple complex camera and movement trajectories for single scenes to evaluate continuity and consistency.
Real-time deployment in interactive environments
Distilled models and efficiency optimizations support deployment in real-time or near-real-time game scenarios.
Integrations
Hugging Face
Project code and model artifacts are referenced via 'Paper Code π€ Hugging Face' on the project page.
Benefits
Limitations
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Frequently Asked Questions
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Getting Started
- 1 Step 1: Read the project paper on arXiv (https://arxiv.org/abs/2506.17201).
- 2 Step 2: Access the project code and assets via the provided 'Paper Code π€ Hugging Face' link on the project page.
- 3 Step 3: Contact the project team for collaboration or internship opportunities ([email protected]).
Support
Primary contact for collaboration and internships: [email protected]
paper
Project paper and method details: https://arxiv.org/abs/2506.17201
code
Project code and assets available via Hugging Face link indicated on the project page ('Paper Code π€ Hugging Face').
API
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