This is an AI video generation application based on LTX 2.3, SDPose pose control, character similarity retention, and third-stage rendering enhancement.
Users only need to upload an action reference video, a character reference image, and input a video prompt. The system will then generate a new video where the character in the reference image completes the actions based on the movements, poses, rhythm, and camera motion in the reference video.
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 character reference 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, character reference 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 magnification, 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 creating dance videos, action transfers, character performances, digital human-controlled videos, AI short drama action shots, talking head action materials, advertising character videos, and short video secondary creation materials.
If packaged into the RunningHub application, the core selling point can be expressed directly as:
Upload an action video and a character image, and generate a three-stage high-definition controlled video with one click.


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