activity
20182023
most citedBEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

202 citations · 475 across the 16 of their papers we have counts for

collaborators

16 papers

cs.LG2023

An Efficient Subgraph GNN with Provable Substructure Counting Power

Zuoyu Yan, Junru Zhou, Liangcai Gao +2

We investigate the enhancement of graph neural networks' (GNNs) representation power through their ability in substructure counting. Recent advances have seen the adoption of subgr…

cs.CV2022★ 1 cited

FlowNAS: Neural Architecture Search for Optical Flow Estimation

Zhiwei Lin, Tingting Liang, Taihong Xiao +3

Existing optical flow estimators usually employ the network architectures typically designed for image classification as the encoder to extract per-pixel features. However, due to…

cs.GR2022

Towards computing complete parameter ranges in parametric modeling

Zhihong Tang, Qiang Zou, Shuming Gao

In parametric design, the geometric model is edited by changing relevant parameters in the parametric model, which is commonly done sequentially on multiple parameters. Without gui…

cs.CV2022★ 202 cited

BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

Tingting Liang, Hongwei Xie, Kaicheng Yu +6

Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to lever…

cs.CG2022★ 5 cited

A review on geometric constraint solving

Qiang Zou, Zhihong Tang, Hsi-Yung Feng +3

This paper presents a comprehensive review of geometric constraint solving in parametric computer-aided design (CAD), with the major focus on its advances in the last 15 years. Geo…

stat.ME2022

Variational design for a structural family of CAD models

Qiang Zou, Qiqiang Zheng, Zhihong Tang +1

Variational design is a well-recognized CAD technique due to the increased design efficiency. It often presents as a parametric family of CAD models. Although effective, this way o…

cs.LG2022★ 2 cited

Neural Approximation of Graph Topological Features

Zuoyu Yan, Tengfei Ma, Liangcai Gao +3

Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods. However, computing extended persistent ho…

astro-ph.IM2021★ 6 cited

The In-Flight Realtime Trigger and Localization Software of GECAM

Xiao-Yun Zhao, Shao-Lin Xiong, Xiang-Yang Wen +86

Realtime trigger and localization of bursts are the key functions of GECAM, which is an all-sky gamma-ray monitor launched in Dec 10, 2020. We developed a multifunctional trigger a…

cs.LG2021★ 5 cited

Cycle Representation Learning for Inductive Relation Prediction

Zuoyu Yan, Tengfei Ma, Liangcai Gao +2

In recent years, algebraic topology and its modern development, the theory of persistent homology, has shown great potential in graph representation learning. In this paper, based…

cs.CV2021★ 177 cited

CBNet: A Composite Backbone Network Architecture for Object Detection

Tingting Liang, Xiaojie Chu, Yudong Liu +5

Modern top-performing object detectors depend heavily on backbone networks, whose advances bring consistent performance gains through exploring more effective network structures. I…

cs.CL2021★ 53 cited

MathBERT: A Pre-Trained Model for Mathematical Formula Understanding

Shuai Peng, Ke Yuan, Liangcai Gao +1

Large-scale pre-trained models like BERT, have obtained a great success in various Natural Language Processing (NLP) tasks, while it is still a challenge to adapt them to the math-…

cs.IR2021

Automatic Description Construction for Math Expression via Topic Relation Graph

Ke Yuan, Zuoyu Yan, Yibo Li +2

Math expressions are important parts of scientific and educational documents, but some of them may be challenging for junior scholars or students to understand. Nevertheless, const…

cs.CV2021★ 2 cited

RPATTACK: Refined Patch Attack on General Object Detectors

Hao Huang, Yongtao Wang, Zhaoyu Chen +3

Nowadays, general object detectors like YOLO and Faster R-CNN as well as their variants are widely exploited in many applications. Many works have revealed that these detectors are…

cs.CV2021★ 5 cited

OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection

Tingting Liang, Yongtao Wang, Zhi Tang +2

Recently, neural architecture search (NAS) has been exploited to design feature pyramid networks (FPNs) and achieved promising results for visual object detection. Encouraged by th…

cs.CV2020★ 3 cited

ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition

Zuoyu Yan, Xiaode Zhang, Liangcai Gao +2

Despite the recent advances in optical character recognition (OCR), mathematical expressions still face a great challenge to recognize due to their two-dimensional graphical layout…

cs.CV2018★ 14 cited

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

Qijie Zhao, Tao Sheng, Yongtao Wang +4

Feature pyramids are widely exploited by both the state-of-the-art one-stage object detectors (e.g., DSSD, RetinaNet, RefineDet) and the two-stage object detectors (e.g., Mask R-CN…