Click To Move: Controlling Video Generation With Sparse Motion

Pierfrancesco Ardino, Marco De Nadai, Bruno Lepri, Elisa Ricci, Stephane Lathuiliere; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 14749-14758

Abstract


This paper introduces Click to Move (C2M), a novel framework for video generation where the user can control the motion of the synthesized video through mouse clicks specifying simple object trajectories of the key objects in the scene. Our model receives as input an initial frame, its corresponding segmentation map and the sparse motion vectors encoding the input provided by the user. It outputs a plausible video sequence starting from the given frame and with a motion that is consistent with user input. Notably, our proposed deep architecture incorporates a Graph Convolution Network (GCN) modelling the movements of all the objects in the scene in a holistic manner and effectively combining the sparse user motion information and image features. Experimental results show that C2M outperforms existing methods on two publicly available datasets, thus demonstrating the effectiveness of our GCN framework at modelling object interactions. The source code is publicly available at https://github.com/PierfrancescoArdino/C2M.

Related Material


[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Ardino_2021_ICCV, author = {Ardino, Pierfrancesco and De Nadai, Marco and Lepri, Bruno and Ricci, Elisa and Lathuiliere, Stephane}, title = {Click To Move: Controlling Video Generation With Sparse Motion}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2021}, pages = {14749-14758} }