SIS-Challenge: Event-Based Spatio-Temporal Instance Segmentation Challenge at the CVPR 2025 Event-Based Vision Workshop

Friedhelm Hamann, Emil Mededovic, Fabian Gülhan, Yue Wu, Johannes Stegmaier, Jing He, Yiqing Wang, Kexin Zhang, Lingling Li, Licheng Jiao, Mengru Ma, Hongxiang Huang, Yuhao Yan, Hongwei Ren, Xiaopeng Lin, Yulong Huang, Bojun Cheng, Se Hyun Lee, Gyu Sung Ham, Kanghan Oh et al. (4 additional authors not shown)

Abstract: 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 accurate pixel-level segmentation masks of defined object classes from spatio-temporally aligned event camera and grayscale camera data. We provide an overview of the task, dataset, challenge details and results. Furthermore, we describe the methods used by the top-5 ranking teams in the challenge. More resources and code of the participants' methods are available here: https://github.com/tubrip/MouseSIS/blob/main/docs/challengeesults.md

External IDs:dblp:conf/iccv/HamannMGWSHWZLJMHYRLHCL25