activity
20202022
most citedRepPoints V2: Verification Meets Regression for Object Detection

70 citations · 151 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2022

Check and Link: Pairwise Lesion Correspondence Guides Mammogram Mass Detection

Ziwei Zhao, Dong Wang, Yihong Chen +2

Detecting mass in mammogram is significant due to the high occurrence and mortality of breast cancer. In mammogram mass detection, modeling pairwise lesion correspondence explicitl…

cs.CV2022

PointScatter: Point Set Representation for Tubular Structure Extraction

Dong Wang, Zhao Zhang, Ziwei Zhao +3

This paper explores the point set representation for tubular structure extraction tasks. Compared with the traditional mask representation, the point set representation enjoys its…

cs.CV2022★ 19 cited

Boosting 3D Object Detection via Object-Focused Image Fusion

Hao Yang, Chen Shi, Yihong Chen +1

3D object detection has achieved remarkable progress by taking point clouds as the only input. However, point clouds often suffer from incomplete geometric structures and the lack…

cs.LG2022★ 5 cited

ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective

Yihong Chen, Pushkar Mishra, Luca Franceschi +3

Factorisation-based Models (FMs), such as DistMult, have enjoyed enduring success for Knowledge Graph Completion (KGC) tasks, often outperforming Graph Neural Networks (GNNs). Howe…

cs.CL2021★ 7 cited

Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations

Yihong Chen, Pasquale Minervini, Sebastian Riedel +1

Learning good representations on multi-relational graphs is essential to knowledge base completion (KBC). In this paper, we propose a new self-supervised training objective for mul…

cs.LG2021★ 20 cited

Learnable Embedding Sizes for Recommender Systems

Siyi Liu, Chen Gao, Yihong Chen +2

The embedding-based representation learning is commonly used in deep learning recommendation models to map the raw sparse features to dense vectors. The traditional embedding manne…

cs.CV2020★ 70 cited

RepPoints V2: Verification Meets Regression for Object Detection

Yihong Chen, Zheng Zhang, Yue Cao +3

Verification and regression are two general methodologies for prediction in neural networks. Each has its own strengths: verification can be easier to infer accurately, and regress…

cs.CV2020★ 30 cited

Memory Enhanced Global-Local Aggregation for Video Object Detection

Yihong Chen, Yue Cao, Han Hu +1

How do humans recognize an object in a piece of video? Due to the deteriorated quality of single frame, it may be hard for people to identify an occluded object in this frame by ju…