The paper introduces SCARF, a real‑time velocity‑invariant representation for event cameras that preserves raw events while handling fast motion, stationary scenes, and independently moving objects. Unlike previous methods that convert events into image‑like forms and lose temporal detail, SCARF maintains temporal information and achieves state‑of‑the‑art performance in computational efficiency and representation quality.
By Mikihiro Ikura, Luna Gava, Jiahang Wu, Chiara Bartolozzi, Arren Glover
arXiv:2606. 14094v1 Announce Type: cross Abstract: Conventional RGB cameras have been widely used in multi-object tracking due to their ability to capture rich appearance and semantic information.
By Shiao Wang, Xiao Wang, Chao Wang, Yitao Li, Menghao Liu, Bo Jiang, Yaowei Wang, Yonghong Tian, Jin Tang
arXiv:2505. 08438v4 Announce Type: replace-cross Abstract: Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes.
By Chuanzhi Xu, Haoxian Zhou, Langyi Chen, Haodong Chen, Zeke Zexi Hu, Zhicheng Lu, Ying Zhou, Vera Chung, Qiang Qu, Weidong Cai
arXiv:2607.05205v2 Announce Type: replace
Abstract: Fast and reliable motion detection is essential for machine vision and autonomous systems operating in dynamic environments. This work integrates e...
By Qinbing Fu, Jingyu Huang, Yan Xie, Jigen Peng, Yuchao Tang
arXiv:2608.24223v1 Announce Type: new
Abstract: Event-based motion estimation is central to tasks that demand high temporal resolution and robustness to fast motion. Existing methods typically rely o...
By Lei Sun, Yuqin Ma, Weilun Li, Haoran Liang, Runyi Yang, Kaiwei Wang, Danda Pani Paudel, Luc Van Gool
arXiv:2603.14023v3 Announce Type: replace
Abstract: This work introduces and demonstrates the first system capable of imaging fast-moving extended non-rigid objects through strong atmospheric turbule...
By Yu-Hsiang Huang, Levi Burner, Sachin Shah, Ziyuan Qu, Adithya Pediredla, Christopher A. Metzler