1 citations · 4 across the 4 of their papers we have counts for
4 papers
Boosting Camera Motion Control for Video Diffusion Transformers
Soon Yau Cheong, Duygu Ceylan, Armin Mustafa +2
Recent advancements in diffusion models have significantly enhanced the quality of video generation. However, fine-grained control over camera pose remains a challenge. While U-Net…
ViscoNet: Bridging and Harmonizing Visual and Textual Conditioning for ControlNet
Soon Yau Cheong, Armin Mustafa, Andrew Gilbert
This paper introduces ViscoNet, a novel one-branch-adapter architecture for concurrent spatial and visual conditioning. Our lightweight model requires trainable parameters and data…
UPGPT: Universal Diffusion Model for Person Image Generation, Editing and Pose Transfer
Soon Yau Cheong, Armin Mustafa, Andrew Gilbert
Text-to-image models (T2I) such as StableDiffusion have been used to generate high quality images of people. However, due to the random nature of the generation process, the person…
KPE: Keypoint Pose Encoding for Transformer-based Image Generation
Soon Yau Cheong, Armin Mustafa, Andrew Gilbert
Transformers have recently been shown to generate high quality images from text input. However, the existing method of pose conditioning using skeleton image tokens is computationa…