Work

Frame-Wise Guided Video Generation for Generative Inbetweening

Year: 2026

Type: preprint

Abstract: Video inbetweening — generating intermediate frames between two given keyframes to produce smooth, temporally coherent video — is a longstanding problem in animation and video production, traditionally requiring skilled manual work or classical interpolation techniques that struggle with large motion or complex scene changes. This project proposes a frame-wise guided video generation approach for generative inbetweening, using deep generative models (e.g., diffusion-based video generators) conditioned on explicit frame-wise guidance signals to produce temporally coherent, high-quality intermediate frames between sparse keyframes.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22021689

Author: GUPTA, ADISHREE

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7203921215

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