12 citations · 27 across the 7 of their papers we have counts for
10 papers
ABCP: Automatic Block-wise and Channel-wise Network Pruning via Joint Search
Jiaqi Li, Haoran Li, Yaran Chen +5
Currently, an increasing number of model pruning methods are proposed to resolve the contradictions between the computer powers required by the deep learning models and the resourc…
MVM3Det: A Novel Method for Multi-view Monocular 3D Detection
Li Haoran, Duan Zicheng, Ma Mingjun +3
Monocular 3D object detection encounters occlusion problems in many application scenarios, such as traffic monitoring, pedestrian monitoring, etc., which leads to serious false neg…
BNAS-v2: Memory-efficient and Performance-collapse-prevented Broad Neural Architecture Search
Zixiang Ding, Yaran Chen, Nannan Li +1
In this paper, we propose BNAS-v2 to further improve the efficiency of NAS, embodying both superiorities of BCNN simultaneously. To mitigate the unfair training issue of BNAS, we e…
ContourRend: A Segmentation Method for Improving Contours by Rendering
Junwen Chen, Yi Lu, Yaran Chen +2
A good object segmentation should contain clear contours and complete regions. However, mask-based segmentation can not handle contour features well on a coarse prediction grid, th…
BiFNet: Bidirectional Fusion Network for Road Segmentation
Haoran Li, Yaran Chen, Qichao Zhang +1
Multi-sensor fusion-based road segmentation plays an important role in the intelligent driving system since it provides a drivable area. The existing mainstream fusion method is ma…
ModuleNet: Knowledge-inherited Neural Architecture Search
Yaran Chen, Ruiyuan Gao, Fenggang Liu +1
Although Neural Architecture Search (NAS) can bring improvement to deep models, they always neglect precious knowledge of existing models. The computation and time costing property…