Furry AI Dance Generator｜KSK Custom Edition

This is a character consistent long video generation workflow built with EverAnimate, Wan2.2 Animate, and loop based video continuation.

The user uploads one reference character image and one driving video. The workflow extracts facial expression, pose motion, timing, and audio from the driving video, then animates the reference character to follow the motion and facial behavior of that video. It first generates the initial segment, automatically calculates how many continuation segments are required from the total frame count, and then uses a for loop to generate the remaining segments before merging everything into a final MP4.

Unlike a standard image to video workflow that only creates a short clip, this pipeline is designed for longer outputs. It divides the source video into 81 frame segments and uses EverAnimate’s first segment and continuation segment structure to preserve character identity, expression continuity, body motion, and temporal consistency across multiple generated clips.

This version is a face and expression reference workflow. It uses a reference image, face video, and pose video, but does not use a background video or character mask. Therefore, it is best suited for character motion transfer, digital human animation, facial expression driving, dance videos, talking character motion reference, anime style character animation, and long video consistency testing. It is not intended for strict background preserving video replacement.

The final output keeps the original driving video’s audio and combines the generated frames into an H.264 MP4 through VideoHelperSuite. The current setup is suitable for 30fps long video generation, character consistent animation, expression driven video, AI digital humans, and EverAnimate continuation

 experiments.

This is a character consistent video generation application based on EverAnimate Wan2.2 Animate long video continuation loop.

Users only need to upload one reference character image and one driving video. The system will automatically extract facial expressions, body poses, motion rhythm, and original audio from the driving video, allowing the reference character to follow the driving video and complete continuous actions. The workflow first generates the initial segment, then automatically calculates the number of continuation segments based on the total frame count of the driving video, uses a for loop to generate subsequent segments, and finally stitches all segments into a complete long video.

Unlike a standard image-to-video workflow that only generates a short clip, this process uses EverAnimate's initial segment and continuation segment structure to divide the long video into multiple 81-frame segments for continuous generation. Each segment integrates the reference character image, face video, pose video, and motion information from the previous segment to maintain consistency in character identity, expression, motion, and segment transitions.

The current version belongs to the emotion/expression reference workflow. It integrates a reference image, face video, and pose video, but does not include a background video or character mask. Therefore, it is more suitable for character motion transfer, digital human expression driving, character dance, talking character motion reference, anime-style character long video generation, and character consistency testing; it is not suitable for strict background-preserving local video replacement.

The final output uses the original driving video’s audio and is synthesized into an H.264 MP4 through VideoHelperSuite. The current configuration is suitable for 30fps long video consistency generation, character motion following, expression-driven video generation, AI digital human videos, and EverAnimate long segment continuation testing.