Generality of SG-I2V beyond Stable Video Diffusion

Ascertain whether SG-I2V (Self-Guided Trajectory Control in Image-to-Video Generation) generalizes from its demonstration on Stable Video Diffusion–specific layers to other image-to-video diffusion backbones, determining the extent to which its trajectory-control mechanism can be applied across architectures.

Background

In discussing training-free motion control approaches, the paper reviews SG-I2V, which replaces spatial self-attention keys/values with those of the first frame and optimizes a latent with a box-restricted similarity loss. The authors note that SG-I2V is demonstrated on SVD-specific layers and explicitly state uncertainty about its generality across other backbones.

Given the importance of plug-and-play methods that work across different image-to-video diffusion architectures, establishing whether SG-I2V’s technique transfers beyond SVD remains an open question highlighted in the paper.

References

This method is demonstrated on SVD-specific layers, so generality for other backbones is unclear; moreover, as shown in Sec. \ref{sec:obj-motion}, it often induces unintended camera motion.

— Time-to-Move: Training-Free Motion Controlled Video Generation via Dual-Clock Denoising  (2511.08633 - Singer et al., 9 Nov 2025) in Section 2 (Related Work, Training-free Motion-controllable video generation)

Moreover, it is not clear how to scale; successful internal guidance at the $\ell$th layer for a small model does not translate to a larger model.

— How to Guide Your Language Flow  (2609.19356 - Dilip et al., 16 Sep 2026) in Appendix, Section “Related work”