33 citations · 115 across the 16 of their papers we have counts for
16 papers
CoBigICP: Robust and Precise Point Set Registration using Correntropy Metrics and Bidirectional Correspondence
Pengyu Yin, Di Wang, Shaoyi Du +3
In this paper, we propose a novel probabilistic variant of iterative closest point (ICP) dubbed as CoBigICP. The method leverages both local geometrical information and global nois…
EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems
Mengli Cheng, Yue Gao, Guoqiang Liu +2
We present EasyRec, an easy-to-use, extendable and efficient recommendation framework for building industrial recommendation systems. Our EasyRec framework is superior in the follo…
MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet
Nan Wang, Shaohui Lin, Xiaoxiao Li +4
U-Nets have achieved tremendous success in medical image segmentation. Nevertheless, it may suffer limitations in global (long-range) contextual interactions and edge-detail preser…
Factored Attention and Embedding for Unstructured-view Topic-related Ultrasound Report Generation
Fuhai Chen, Rongrong Ji, Chengpeng Dai +4
Echocardiography is widely used to clinical practice for diagnosis and treatment, e.g., on the common congenital heart defects. The traditional manual manipulation is error-prone d…
3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds
Junsheng Zhou, Xin Wen, Baorui Ma +4
The manual annotation for large-scale point clouds is still tedious and unavailable for many harsh real-world tasks. Self-supervised learning, which is used on raw and unlabeled da…
Experimental Security Analysis of the App Model in Business Collaboration Platforms
Yunang Chen, Yue Gao, Nick Ceccio +3
Business Collaboration Platforms like Microsoft Teams and Slack enable teamwork by supporting text chatting and third-party resource integration. A user can access online file stor…
View-Guided Point Cloud Completion
Xuancheng Zhang, Yutong Feng, Siqi Li +5
This paper presents a view-guided solution for the task of point cloud completion. Unlike most existing methods directly inferring the missing points using shape priors, we address…
ReCU: Reviving the Dead Weights in Binary Neural Networks
Zihan Xu, Mingbao Lin, Jianzhuang Liu +5
Binary neural networks (BNNs) have received increasing attention due to their superior reductions of computation and memory. Most existing works focus on either lessening the quant…
Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network
Jiayi Ji, Yunpeng Luo, Xiaoshuai Sun +5
Transformer-based architectures have shown great success in image captioning, where object regions are encoded and then attended into the vectorial representations to guide the cap…
Attention-based Multi-modal Fusion Network for Semantic Scene Completion
Siqi Li, Changqing Zou, Yipeng Li +2
This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the o…
Deep Multi-View Enhancement Hashing for Image Retrieval
Chenggang Yan, Biao Gong, Yuxuan Wei +1
Hashing is an efficient method for nearest neighbor search in large-scale data space by embedding high-dimensional feature descriptors into a similarity preserving Hamming space wi…
PVRNet: Point-View Relation Neural Network for 3D Shape Recognition
Haoxuan You, Yifan Feng, Xibin Zhao +3
Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D featu…
Universal Perturbation Attack Against Image Retrieval
Jie Li, Rongrong Ji, Hong Liu +3
Universal adversarial perturbations (UAPs), a.k.a. input-agnostic perturbations, has been proved to exist and be able to fool cutting-edge deep learning models on most of the data…
MeshNet: Mesh Neural Network for 3D Shape Representation
Yutong Feng, Yifan Feng, Haoxuan You +2
Mesh is an important and powerful type of data for 3D shapes and widely studied in the field of computer vision and computer graphics. Regarding the task of 3D shape representation…
Hypergraph Neural Networks
Yifan Feng, Haoxuan You, Zizhao Zhang +2
In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure. Co…
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition
Haoxuan You, Yifan Feng, Rongrong Ji +1
3D object recognition has attracted wide research attention in the field of multimedia and computer vision. With the recent proliferation of deep learning, various deep models with…