FeaCo: Reaching Robust Feature-Level Consensus in Noisy Pose Conditions. Collaborative perception offers a promising solution to overcome challenges such as occlusion and long-range data processing. However, limited sensor accuracy leads to noisy poses that misalign observations among vehicles.
Oct 28, 2024
Oct 27, 2023 · We propose the FeaCo, which achieves robust Feature-level Consensus among collaborating agents in noisy pose conditions without additional training.
Oct 29, 2023 · It can overcome the inherent limitations of single-agentbased perception, such as invisibility caused by occlusion or longrange issues.
We propose the FeaCo, which achieves robust Feature-level Consensus among collaborating agents in noisy pose conditions without additional training.
FeaCo: Reaching Robust Feature-Level Consensus in Noisy Pose Conditions. J Gu*, J Zhang* (Co-first author), M Zhang, W Meng, S Xu, J Zhang, ... Proceedings ...
FeaCo: Reaching Robust Feature-Level Consensus in Noisy Pose Conditions. 2023-10-26 | Conference paper. DOI: 10.1145/3581783.3611880. Contributors: Jiaming Gu ...
This paper introduces RoCo, an unsupervised framework for iterative object matching and agent pose adjustment in collaborative perception scenarios.
Apr 20, 2024 · ... Feaco: Reaching robust feature-level consensus in noisy pose conditions. In: Proceedings of the 31st ACM International Conference on ...
FeaCo: Reaching Robust Feature-Level Consensus in Noisy Pose Conditions. ACM ... Visual Reconstruction and Localization-Based Robust Robotic 6-DoF Grasping in the ...
This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.