Zobrazeno 1 - 10
of 304
pro vyhledávání: '"Ma, Junyi"'
Place recognition is a crucial module to ensure autonomous vehicles obtain usable localization information in GPS-denied environments. In recent years, multimodal place recognition methods have gained increasing attention due to their ability to over
Externí odkaz:
http://arxiv.org/abs/2410.00299
Autor:
Gan, Rui, Shi, Haotian, Li, Pei, Wu, Keshu, An, Bocheng, Li, Linheng, Ma, Junyi, Ma, Chengyuan, Ran, Bin
Vehicle trajectory prediction plays a vital role in intelligent transportation systems and autonomous driving, as it significantly affects vehicle behavior planning and control, thereby influencing traffic safety and efficiency. Numerous studies have
Externí odkaz:
http://arxiv.org/abs/2409.15182
Understanding human intentions and actions through egocentric videos is important on the path to embodied artificial intelligence. As a branch of egocentric vision techniques, hand trajectory prediction plays a vital role in comprehending human motio
Externí odkaz:
http://arxiv.org/abs/2409.02638
Understanding how humans would behave during hand-object interaction is vital for applications in service robot manipulation and extended reality. To achieve this, some recent works have been proposed to simultaneously forecast hand trajectories and
Externí odkaz:
http://arxiv.org/abs/2405.04370
Fusion-based place recognition is an emerging technique jointly utilizing multi-modal perception data, to recognize previously visited places in GPS-denied scenarios for robots and autonomous vehicles. Recent fusion-based place recognition methods co
Externí odkaz:
http://arxiv.org/abs/2402.17264
Large-scale 3D scene reconstruction and novel view synthesis are vital for autonomous vehicles, especially utilizing temporally sparse LiDAR frames. However, conventional explicit representations remain a significant bottleneck towards representing t
Externí odkaz:
http://arxiv.org/abs/2402.09325
Autor:
Ma, Junyi, Chen, Xieyuanli, Huang, Jiawei, Xu, Jingyi, Luo, Zhen, Xu, Jintao, Gu, Weihao, Ai, Rui, Wang, Hesheng
Understanding how the surrounding environment changes is crucial for performing downstream tasks safely and reliably in autonomous driving applications. Recent occupancy estimation techniques using only camera images as input can provide dense occupa
Externí odkaz:
http://arxiv.org/abs/2311.17663
Place recognition is one of the most crucial modules for autonomous vehicles to identify places that were previously visited in GPS-invalid environments. Sensor fusion is considered an effective method to overcome the weaknesses of individual sensors
Externí odkaz:
http://arxiv.org/abs/2311.03198
Reconstructing large-scale 3D scenes is essential for autonomous vehicles, especially when partial sensor data is lost. Although the recently developed neural radiance fields (NeRF) have shown compelling results in implicit representations, the large
Externí odkaz:
http://arxiv.org/abs/2310.00874
The ability to predict future structure features of environments based on past perception information is extremely needed by autonomous vehicles, which helps to make the following decision-making and path planning more reasonable. Recently, point clo
Externí odkaz:
http://arxiv.org/abs/2304.07773