11 citations · 32 across the 15 of their papers we have counts for
6 papers · 1 filter
STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation
Yupeng Zheng, Chengliang Zhong, Pengfei Li +8
Self-supervised depth estimation draws a lot of attention recently as it can promote the 3D sensing capabilities of self-driving vehicles. However, it intrinsically relies upon the…
BViT: Broad Attention based Vision Transformer
Nannan Li, Yaran Chen, Weifan Li +2
Recent works have demonstrated that transformer can achieve promising performance in computer vision, by exploiting the relationship among image patches with self-attention. While…
Stacked BNAS: Rethinking Broad Convolutional Neural Network for Neural Architecture Search
Zixiang Ding, Yaran Chen, Nannan Li +2
Different from other deep scalable architecture-based NAS approaches, Broad Neural Architecture Search (BNAS) proposes a broad scalable architecture which consists of convolution a…
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…
Complementary Feature Enhanced Network with Vision Transformer for Image Dehazing
Dong Zhao, Jia Li, Hongyu Li +1
Conventional CNNs-based dehazing models suffer from two essential issues: the dehazing framework (limited in interpretability) and the convolution layers (content-independent and i…