Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Miao, Zhenwei"'
Microscopic traffic simulation plays a crucial role in transportation engineering by providing insights into individual vehicle behavior and overall traffic flow. However, creating a realistic simulator that accurately replicates human driving behavi
Externí odkaz:
http://arxiv.org/abs/2403.17601
Point cloud panoptic segmentation is a challenging task that seeks a holistic solution for both semantic and instance segmentation to predict groupings of coherent points. Previous approaches treat semantic and instance segmentation as surrogate task
Externí odkaz:
http://arxiv.org/abs/2302.06185
Autor:
Xu, Jianyun, Miao, Zhenwei, Zhang, Da, Pan, Hongyu, Liu, Kaixuan, Hao, Peihan, Zhu, Jun, Sun, Zhengyang, Li, Hongmin, Zhan, Xin
It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their
Externí odkaz:
http://arxiv.org/abs/2209.15215
Existing top-performance 3D object detectors typically rely on the multi-modal fusion strategy. This design is however fundamentally restricted due to overlooking the modality-specific useful information and finally hampering the model performance. T
Externí odkaz:
http://arxiv.org/abs/2208.11112
3D object detection in autonomous driving aims to reason "what" and "where" the objects of interest present in a 3D world. Following the conventional wisdom of previous 2D object detection, existing methods often adopt the canonical Cartesian coordin
Externí odkaz:
http://arxiv.org/abs/2206.15398
In this paper, an adaptive pixel ternary coding mechanism is proposed and a contrast invariant and noise resistant interest point detector is developed on the basis of this mechanism. Every pixel in a local region is adaptively encoded into one of th
Externí odkaz:
http://arxiv.org/abs/1901.00031
Local feature descriptors have been widely used in fine-grained visual object search thanks to their robustness in scale and rotation variation and cluttered background. However, the performance of such descriptors drops under severe illumination cha
Externí odkaz:
http://arxiv.org/abs/1901.00027
Publikováno v:
In Computer Vision and Image Understanding October 2022 223
Autor:
Zhang, Xinfang, Eichen, Yoav, Miao, Zhenwei, Zhang, Shuangkun, Cai, Qing, Liu, Wei, Zhao, Jingbo, Wu, Zhanpeng
Publikováno v:
In Chemical Engineering Journal 15 July 2022 440