23 citations · 48 across the 20 of their papers we have counts for
7 papers · 1 filter
SelfMOTR: Revisiting MOTR with Self-Generating Detection Priors
Fabian Gülhan, Emil Mededovic, Yuli Wu +1
End-to-end transformer architectures have driven significant progress in multi-object tracking by unifying detection and association into a single, heuristic-free framework. Despit…
SIS-Challenge: Event-based Spatio-temporal Instance Segmentation Challenge at the CVPR 2025 Event-based Vision Workshop
Friedhelm Hamann, Emil Mededovic, Fabian Gülhan +21
We present an overview of the Spatio-temporal Instance Segmentation (SIS) challenge held in conjunction with the CVPR 2025 Event-based Vision Workshop. The task is to predict accur…
Eye on the Target: Eye Tracking Meets Rodent Tracking
Emil Mededovic, Yuli Wu, Henning Konermann +4
Analyzing animal behavior from video recordings is crucial for scientific research, yet manual annotation remains labor-intensive and prone to subjectivity. Efficient segmentation…
CellStyle: Improved Zero-Shot Cell Segmentation via Style Transfer
Rüveyda Yilmaz, Zhu Chen, Yuli Wu +1
Cell microscopy data are abundant; however, corresponding segmentation annotations remain scarce. Moreover, variations in cell types, imaging devices, and staining techniques intro…
Evaluating Cross-Subject and Cross-Device Consistency in Visual Fixation Prediction
Yuli Wu, Henning Konermann, Emil Mededovic +2
Understanding cross-subject and cross-device consistency in visual fixation prediction is essential for advancing eye-tracking applications, including visual attention modeling and…
No Free Lunch in Annotation either: An objective evaluation of foundation models for streamlining annotation in animal tracking
Emil Mededovic, Valdy Laurentius, Yuli Wu +5
We analyze the capabilities of foundation models addressing the tedious task of generating annotations for animal tracking. Annotating a large amount of data is vital and can be a…
A Pragmatic Note on Evaluating Generative Models with Fréchet Inception Distance for Retinal Image Synthesis
Yuli Wu, Fucheng Liu, Rüveyda Yilmaz +3
Fréchet Inception Distance (FID), computed with an ImageNet pretrained Inception-v3 network, is widely used as a state-of-the-art evaluation metric for generative models. It assume…