activity
20162020
most citedR2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection

490 citations · 1.1k across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2020★ 43 cited

Physically-Constrained Transfer Learning through Shared Abundance Space for Hyperspectral Image Classification

Ying Qu, Razieh Kaviani Baghbaderani, Wei Li +2

Hyperspectral image (HSI) classification is one of the most active research topics and has achieved promising results boosted by the recent development of deep learning. However, m…

cs.CV2020★ 17 cited

Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor

Wensheng Cheng, Hao Luo, Wen Yang +2

Lane marker extraction is a basic yet necessary task for autonomous driving. Although past years have witnessed major advances in lane marker extraction with deep learning models,…

cs.CV2020★ 58 cited

Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network

Xin Wu, Wei Li, Danfeng Hong +3

Vehicle detection in remote sensing images has attracted increasing interest in recent years. However, its detection ability is limited due to lack of well-annotated samples, espec…

cs.CV2020★ 4 cited

PerMO: Perceiving More at Once from a Single Image for Autonomous Driving

Feixiang Lu, Zongdai Liu, Xibin Song +8

We present a novel approach to detect, segment, and reconstruct complete textured 3D models of vehicles from a single image for autonomous driving. Our approach combines the streng…

cs.CV2019★ 218 cited

Spatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification

Wen-Shuai Hu, Heng-Chao Li, Lei Pan +3

In recent years, deep learning has presented a great advance in hyperspectral image (HSI) classification. Particularly, long short-term memory (LSTM), as a special deep learning st…

cs.CV2017★ 36 cited

Attribute Recognition by Joint Recurrent Learning of Context and Correlation

Jingya Wang, Xiatian Zhu, Shaogang Gong +1

Recognising semantic pedestrian attributes in surveillance images is a challenging task for computer vision, particularly when the imaging quality is poor with complex background c…