173 citations · 228 across the 10 of their papers we have counts for
9 papers · 1 filter
Modeling Continuous Motion for 3D Point Cloud Object Tracking
Zhipeng Luo, Gongjie Zhang, Changqing Zhou +4
The task of 3D single object tracking (SOT) with LiDAR point clouds is crucial for various applications, such as autonomous driving and robotics. However, existing approaches have…
ReCasNet: Improving consistency within the two-stage mitosis detection framework
Chawan Piansaddhayanon, Sakun Santisukwongchote, Shanop Shuangshoti +3
Mitotic count (MC) is an important histological parameter for cancer diagnosis and grading, but the manual process for obtaining MC from whole-slide histopathological images is ver…
Medical Visual Question Answering: A Survey
Zhihong Lin, Donghao Zhang, Qingyi Tao +5
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in…
Exploring Bottom-up and Top-down Cues with Attentive Learning for Webly Supervised Object Detection
Zhonghua Wu, Qingyi Tao, Guosheng Lin +1
Fully supervised object detection has achieved great success in recent years. However, abundant bounding boxes annotations are needed for training a detector for novel classes. To…
Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention
Qingyi Tao, Zongyuan Ge, Jianfei Cai +2
Lesion detection from computed tomography (CT) scans is challenging compared to natural object detection because of two major reasons: small lesion size and small inter-class varia…
M2E-Try On Net: Fashion from Model to Everyone
Zhonghua Wu, Guosheng Lin, Qingyi Tao +1
Most existing virtual try-on applications require clean clothes images. Instead, we present a novel virtual Try-On network, M2E-Try On Net, which transfers the clothes from a model…
VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions
Qing Li, Qingyi Tao, Shafiq Joty +2
Most existing works in visual question answering (VQA) are dedicated to improving the accuracy of predicted answers, while disregarding the explanations. We argue that the explanat…
Zero-Annotation Object Detection with Web Knowledge Transfer
Qingyi Tao, Hao Yang, Jianfei Cai
Object detection is one of the major problems in computer vision, and has been extensively studied. Most of the existing detection works rely on labor-intensive supervision, such a…
Exploiting Web Images for Weakly Supervised Object Detection
Qingyi Tao, Hao Yang, Jianfei Cai
In recent years, the performance of object detection has advanced significantly with the evolving deep convolutional neural networks. However, the state-of-the-art object detection…