5 citations · 7 across the 7 of their papers we have counts for
10 papers
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…
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
Beyond the LUMIR challenge: The pathway to foundational registration models
Junyu Chen, Shuwen Wei, Joel Honkamaa +33
Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. Image registration, a foundati…
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…
Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time Series
Onur Poyraz, Pekka Marttinen
Analysis of multivariate healthcare time series data is inherently challenging: irregular sampling, noisy and missing values, and heterogeneous patient groups with different dynami…
Identifiable causal inference with noisy treatment and no side information
Antti Pöllänen, Pekka Marttinen
In some causal inference scenarios, the treatment variable is measured inaccurately, for instance in epidemiology or econometrics. Failure to correct for the effect of this measure…
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…
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models
Severi Rissanen, Pekka Marttinen
Using deep latent variable models in causal inference has attracted considerable interest recently, but an essential open question is their ability to yield consistent causal estim…