This is an AI video generation application based on LTX 2.3, SDPose pose control, character similarity preservation, and three-stage rendering enhancement.
Users only need to upload a reference action video, a reference character image, and input a video prompt. The system will generate a new video where the character in the reference image performs the actions from the reference video, including its poses, rhythms, and camera movements.
Unlike ordinary image-to-video generation, this process does not simply animate a static image randomly. Instead, it uses the reference video for precise control. The reference video provides the actions and motion rhythm, the reference character image locks in the character's identity, facial features, hairstyle, clothing, and overall appearance, while the prompt controls the video content, scene style, and visual atmosphere.
The entire process is automated: reference video reading, reference character image reading, video frame rate and frame count recognition, reference video preprocessing, SDPose pose extraction, character image anchoring, face detection, first-stage high similarity generation, second-stage latent space amplification, third-stage high-definition refinement, audio latent processing, video decoding, and final MP4 output.
The final output is a video where the actions are controlled by the reference video, the character closely matches the reference image, and the visuals are enhanced through three stages. It is suitable for generating character dance videos, action transfer, role performances, digital character control videos, AI short drama action shots, talking head action materials, advertising character videos, and short video secondary creation materials.
If packaged as a RunningHub application, the core selling point can be directly expressed as:
Upload an action video and a character image, and generate a three-stage high-definition control video with one click.


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