arXiv Computer Vision
2d ago

FAST: Flow Any Scene Transformer

arXiv:2609.39748v1 Announce Type: new Abstract: Scaling has become a primary driver of progress in language and vision foundation models, yet its role in precise correspondence matching remains under...

By Yongjian Zhang, Longguang Wang, Zhuo Song, Zhiheng Fu, Liang Lin, Yulan Guo
arXiv Computer Vision
Sep 23

Moving6DPoSe: A Multimodal Database for Monocular 6D Pose Estimation and Segmentation of Moving Objects

Moving6DPoSe is a multimodal database for monocular 6D pose estimation and segmentation of moving objects, comprising two subsets: real-world recordings (Moving6DPoSe‑R) and synthetic sequences (Moving6DPoSe‑S). It includes 16 scanned objects, 1,702 real and synthetic rosbags, and annotations for semantic segmentation, object detection, and monocular 6D pose estimation. Baseline results show that event-based representations outperform conventional RGB images for moving‑object segmentation, while monocular orientation estimation remains challenging.

By Ignacio Bugueno-Cordova, Javier Ruiz-del-Solar, Rodrigo Verschae