6 papers
MobileWan: Closing the Quality Gap for Mobile Video Diffusion
Mohsen Ghafoorian, Denis Korzhenkov, Adil Karjauv +9
Recent advances in video diffusion have been driven by scaling transformer-based architectures to billions of parameters, substantially improving visual fidelity and motion coheren…
PyramidalWan: On Making Pretrained Video Model Pyramidal for Efficient Inference
Denis Korzhenkov, Adil Karjauv, Animesh Karnewar +2
Recently proposed pyramidal models decompose the conventional forward and backward diffusion processes into multiple stages operating at varying resolutions. These models handle in…
Attention Surgery: An Efficient Recipe to Linearize Your Video Diffusion Transformer
Mohsen Ghafoorian, Denis Korzhenkov, Amirhossein Habibian
Transformer-based video diffusion models (VDMs) deliver state-of-the-art video generation quality but are constrained by the quadratic cost of self-attention, making long sequences…
Neodragon: Mobile Video Generation using Diffusion Transformer
Animesh Karnewar, Denis Korzhenkov, Ioannis Lelekas +10
We introduce Neodragon, a text-to-video system capable of generating 2s (49 frames @24 fps) videos at the 640x1024 resolution directly on a Qualcomm Hexagon NPU in a record 6.7s (7…
MoAlign: Motion-Centric Representation Alignment for Video Diffusion Models
Aritra Bhowmik, Denis Korzhenkov, Cees G. M. Snoek +2
Text-to-video diffusion models have enabled high-quality video synthesis, yet often fail to generate temporally coherent and physically plausible motion. A key reason is the models…
Mobile Video Diffusion
Haitam Ben Yahia, Denis Korzhenkov, Ioannis Lelekas +2
Video diffusion models have achieved impressive realism and controllability but are limited by high computational demands, restricting their use on mobile devices. This paper intro…