arXiv:2607. 23910v1 Announce Type: cross Abstract: Cooperative perception through vehicle-to-everything (V2X) communication can overcome the inherent physical limitations of individual autonomous vehicles, such as occlusions and limited sensor range.
By Goodarz Mehr, Sepideh Gohari, Montasir Abbas, Azim Eskandarian
The paper introduces TADP, a task‑aware deformable prediction framework for single‑stage 3D object detection. It employs a triple feature refinement aggregation module, a multi‑scale feature aggregation block, and a plug‑and‑play task‑aware deformation head to adaptively extract and fuse features for different detection tasks. Experiments on the KITTI dataset show that TADP achieves a car mAP of 80.91%, outperforming many state‑of‑the‑art methods.
By Su Wang, Yaochen Li, Min Yang, Jiaohao Nie, Chang Liu, Yuehu Liu
arXiv:2608.13147v2 Announce Type: replace
Abstract: Camera-based autonomous driving perception requires a shared representation that preserves metric 3D structure across synchronized multi-camera str...
By Longfei Xu, Xiaohui Wang, Zehao Huang, Han Li, Ya Yang, Naiyan Wang, Si Liu
arXiv:2608. 19973v1 Announce Type: cross Abstract: Recently, open-vocabulary 3D object detection (3D-OVD) has gained increasing attention for its ability to detect unseen objects in 3D scenes.
By Shangbo Yuan, Jie Xu, Xiaofeng Zhu, Na Zhao
arXiv:2605. 20301v2 Announce Type: replace-cross Abstract: In autonomous driving, 3D object detection is essential for accurate perception and reliable decision-making.
By Wenxuan Li, Qin Zou, Shoubing Chen, Chi Chen, Yingyi Yang, Qingxiang Meng
arXiv:2608.21136v1 Announce Type: new
Abstract: Recently, open-vocabulary zero-shot 3D scene understanding using vision foundation models has emerged as a promising alternative to data-intensive supe...
By Jie Xu, Na Zhao