44 citations
- Tsinghua UniversityCN4 papers
- Huazhong University of Science and TechnologyCN3 papers
- Chinese Academy of SciencesCN2 papers
- Institute of AutomationCN2 papers
- Nanjing UniversityCN2 papers
- Beijing University of Posts and TelecommunicationsCN1 paper
- Central South UniversityCN1 paper
- Chinese University of Hong KongHK1 paper
- Horizon Research (United States)US1 paper
- Institute of AcousticsCN1 paper
- Ludwig-Maximilians-Universität MünchenDE1 paper
- Peking UniversityCN1 paper
11 papers · 1 filter
Towards Accurate Ground Plane Normal Estimation from Ego-Motion
Jiaxin Zhang, Wei Sui, Qian Zhang +2
In this paper, we introduce a novel approach for ground plane normal estimation of wheeled vehicles. In practice, the ground plane is dynamically changed due to braking and unstabl…
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative Transformer
Jiaqi Ma, Shengyuan Yan, Lefei Zhang +2
In order to get raw images of high quality for downstream Image Signal Process (ISP), in this paper we present an Efficient Locally Multiplicative Transformer called ELMformer for…
Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation
Xinggang Wang, Zhaojin Huang, Bencheng Liao +3
Video object detection is a fundamental problem in computer vision and has a wide spectrum of applications. Based on deep networks, video object detection is actively studied for p…
Learning to Focus: Cascaded Feature Matching Network for Few-shot Image Recognition
Mengting Chen, Xinggang Wang, Heng Luo +2
Deep networks can learn to accurately recognize objects of a category by training on a large number of annotated images. However, a meta-learning challenge known as a low-shot imag…
Gaussian Vector: An Efficient Solution for Facial Landmark Detection
Yilin Xiong, Zijian Zhou, Yuhao Dou +1
Significant progress has been made in facial landmark detection with the development of Convolutional Neural Networks. The widely-used algorithms can be classified into coordinate…
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
Yiqun Mei, Yuchen Fan, Yuqian Zhou +3
Deep convolution-based single image super-resolution (SISR) networks embrace the benefits of learning from large-scale external image resources for local recovery, yet most existin…