5 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
Why Cross-Skeleton Retargeting Is Non-Identifiable: Structural Limits of Generative Motion Models
Zhiyuan Li, Wenyan Yang, Pekka Marttinen +1
Cross-skeleton motion generation trains generative models to carry action structure and motion intention from one body to another. Yet a target motion that shows the right action h…
Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence
Zhiyuan Li, Rongzhen Zhao, Wenyan Yang +3
The de facto approach in video object-centric learning maintains temporal consistency through learned dynamics modules that predict future object representations, called slots. We…
Strategies for Robust Deep Learning Based Deformable Registration
Joel Honkamaa, Pekka Marttinen
Deep learning based deformable registration methods have become popular in recent years. However, their ability to generalize beyond training data distribution can be poor, signifi…
New multimodal similarity measure for image registration via modeling local functional dependence with linear combination of learned basis functions
Joel Honkamaa, Pekka Marttinen
The deformable registration of images of different modalities, essential in many medical imaging applications, remains challenging. The main challenge is developing a robust measur…
Deformation equivariant cross-modality image synthesis with paired non-aligned training data
Joel Honkamaa, Umair Khan, Sonja Koivukoski +4
Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications. Recently, methods allowing training with paired but misaligned da…