Video Body Shape Adjustment With Temporal Consistency Control
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Solution Overview
Problem
Existing body shape adjustment methods in video processing often result in sudden changes and poor temporal consistency, leading to undesirable effects such as background jumps and large shape changes between adjacent frames.
Innovation Solution
A video generation method that includes body shape parameter prediction and adjustment for each frame, followed by generating a second video based on these adjustments, ensuring that frame positions in the second video are within a preset distance threshold of their corresponding frames in the first video, utilizing a model with image-level and time sequence modules for attention processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If body shape adjustment is performed on each frame independently, then body shape adjustment flexibility is improved, but temporal consistency deteriorates causing sudden changes and background jumps
Solution Approach 1:
The video processing is segmented into two distinct modules: an image-level processing module that handles body shape adjustment for each frame independently, and a time sequence module that processes multiple frames to ensure temporal consistency. This segmentation allows each module to specialize in its function while working together to resolve the contradiction between adjustment flexibility and temporal consistency.
Solution Approach 2:
The time sequence module acts as an intermediary between independently processed frames. It receives adjustment results from the image-level module and mediates them by performing attention processing in the time direction, ensuring that transitions between frames are smooth and temporally consistent while preserving the body shape adjustment flexibility provided by the image-level module.
2Stability of the object's composition
If multiple frame images are used for generating each output frame, then temporal consistency is improved, but computational complexity increases
Solution Approach 1:
Body shape parameter prediction and adjustment are performed in advance for each frame by the image-level processing module before the time sequence module processes them. This preliminary action prepares the data in a way that reduces the computational burden on the time sequence module, allowing it to focus on temporal consistency without excessive computational complexity.
Solution Approach 2:
The time sequence module applies attention processing selectively to ensure temporal consistency where needed, rather than uniformly processing all frames with the same computational intensity. This partial action approach maintains temporal consistency while avoiding unnecessary computational complexity in regions where it is less critical.
3Manufacturing precision
If body shape parameters are adjusted significantly, then body shape adjustment effect is improved, but visual naturalness deteriorates causing noticeable artifacts
Solution Approach 1:
The time sequence module provides feedback to the image-level processing by performing attention processing on the adjustment results across multiple frames. This feedback mechanism ensures that significant body shape adjustments maintain visual naturalness by comparing and coordinating changes across the video sequence, preventing noticeable artifacts while preserving adjustment precision.
Data Source
AI summary
The disclosure discloses a video generation method, an apparatus, a device, a medium and a product. The method comprises: firstly, obtaining a first video so that at least one frame image in the first video includes a target object; then, for any frame image in the first video, performing body shape parameter prediction processing on the image to obtain the body shape parameter prediction result corresponding to the image, and performing adjustment processing on the body shape parameter prediction result corresponding to the image based on the body shape adjustment information specified for the target object to obtain the body shape parameter adjustment result corresponding to the image; finally, generating a second video based on the first video and the body shape parameter adjustment result corresponding to at least one image in the first video.