2.3k citations
- Chinese Academy of SciencesCN7 papers
- Southern University of Science and TechnologyCN7 papers
- Mohamed bin Zayed University of Artificial IntelligenceAE5 papers
- University of Electronic Science and Technology of ChinaCN5 papers
- Harbin Institute of TechnologyCN4 papers
- Nanjing University of Science and TechnologyCN4 papers
- Nankai UniversityCN4 papers
- Sun Yat-sen UniversityCN4 papers
- Tianjin UniversityCN4 papers
- University of AmsterdamNL4 papers
- Wuhan UniversityCN4 papers
- Australian National UniversityAU3 papers
53 papers
Adaptive Siamese Tracking with a Compact Latent Network
Xingping Dong, Jianbing Shen, Fatih Porikli +2
In this paper, we provide an intuitive viewing to simplify the Siamese-based trackers by converting the tracking task to a classification. Under this viewing, we perform an in-dept…
Outlier-based Autism Detection using Longitudinal Structural MRI
Devika K, Venkata Ramana Murthy Oruganti, Dwarikanath Mahapatra +1
Diagnosis of Autism Spectrum Disorder (ASD) using clinical evaluation (cognitive tests) is challenging due to wide variations amongst individuals. Since no effective treatment exis…
From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder
Jiale Li, Hang Dai, Ling Shao +1
In this paper, we present an Intersection-over-Union (IoU) guided two-stage 3D object detector with a voxel-to-point decoder. To preserve the necessary information from all raw poi…
Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud
Jiale Li, Hang Dai, Ling Shao +1
Most of the existing single-stage and two-stage 3D object detectors are anchor-based methods, while the efficient but challenging anchor-free single-stage 3D object detection is no…
From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data
Ye Liu, Lei Zhu, Shunda Pei +5
Single image dehazing is a challenging task, for which the domain shift between synthetic training data and real-world testing images usually leads to degradation of existing metho…
Kernel Continual Learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao +1
This paper introduces kernel continual learning, a simple but effective variant of continual learning that leverages the non-parametric nature of kernel methods to tackle catastrop…