EcoVideo: Entropy-Orchestrated Video Generation Paradigm in Cloud-Edge Dynamics

• URL: http://arxiv.org/abs/2606.30557v1
• Date: Mon, 29 Jun 2026 16:51:56 GMT
• Title: EcoVideo: Entropy-Orchestrated Video Generation Paradigm in Cloud-Edge Dynamics
• Abstract summary: We propose EcoVideo, an entropy-orchestrated framework for dynamic inter-frame decoupling.<n>We show improved quality-efficiency trade-offs and up to 2.9x end-to-end speedup in low-bandwidth, compute-limited edge settings.
• Score: 15.798324066707105
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: DiT video generation is latency-intensive due to iterative full-frame denoising, while prior cloud-edge methods largely rely on static inter-step decoupling and cannot leverage inter-frame similarity or adapt to system dynamics. We propose EcoVideo, an entropy-orchestrated framework for dynamic inter-frame decoupling: early-stage self-attention entropy provides a training-free estimate of frame-wise information density for frame selection; a cloud large model denoises sparse high-entropy keyframes; and an edge lightweight model reconstructs the remaining frames via motion-aware interpolation with refinement for temporal stability. EcoVideo further adapts the keyframe budget and edge refinement depth to real-time bandwidth and compute availability, optimizing end-to-end latency under constraints. Experiments on representative DiT video generators show improved quality--efficiency trade-offs and up to 2.9x end-to-end speedup in low-bandwidth, compute-limited edge settings. Code is available at https://github.com/IF-LAB-PKU/EcoVideo.

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