Search Results for author: Xiaoping Li

Found 16 papers, 7 papers with code

Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking

no code implementations23 Aug 2022 Jinrong Yang, En Yu, Zeming Li, Xiaoping Li, Wenbing Tao

Recent advanced works generally employ a series of object attributes, e. g., position, size, velocity, and appearance, to provide the clues for the association in 3D MOT.

3D Multi-Object Tracking 3D Object Detection +1

DBQ-SSD: Dynamic Ball Query for Efficient 3D Object Detection

1 code implementation22 Jul 2022 Jinrong Yang, Lin Song, Songtao Liu, Weixin Mao, Zeming Li, Xiaoping Li, Hongbin Sun, Jian Sun, Nanning Zheng

Many point-based 3D detectors adopt point-feature sampling strategies to drop some points for efficient inference.

3D Object Detection object-detection

StreamYOLO: Real-time Object Detection for Streaming Perception

no code implementations21 Jul 2022 Jinrong Yang, Songtao Liu, Zeming Li, Xiaoping Li, Jian Sun

In this paper, we explore the performance of real time models on this metric and endow the models with the capacity of predicting the future, significantly improving the results for streaming perception.

Autonomous Driving object-detection +1

Real-time Object Detection for Streaming Perception

1 code implementation CVPR 2022 Jinrong Yang, Songtao Liu, Zeming Li, Xiaoping Li, Jian Sun

In this paper, instead of searching trade-offs between accuracy and speed like previous works, we point out that endowing real-time models with the ability to predict the future is the key to dealing with this problem.

 Ranked #1 on Real-Time Object Detection on Argoverse-HD (Full-Stack, Val) (sAP metric, using extra training data)

Autonomous Driving object-detection +1

Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT

1 code implementation3 Feb 2022 Zonghang Li, Yihong He, Hongfang Yu, Jiawen Kang, Xiaoping Li, Zenglin Xu, Dusit Niyato

In this paper, we propose FedGS, which is a hierarchical cloud-edge-end FL framework for 5G empowered industries, to improve industrial FL performance on non-i. i. d.

Federated Learning

Performance assessment and tuning of PID control using TLBO: the single-loop case and PI/P cascade case

no code implementations31 Jul 2021 Wei zhang, He Dong, Yunlang Xu, Xiaoping Li

Minimum output variance (MOV) is used as a benchmark for CPA of PID, but it is difficult to be found due to the associated non-convex optimization problem.

Stochastic Optimization

Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection

no code implementations25 Mar 2021 Shengkai Wu, Jinrong Yang, Hangcheng Yu, Lijun Gou, Xiaoping Li

This results in two problems: (1) only one anchor is assigned to most of the slender objects which leads to insufficient supervision information for the slender objects during training and the performance on the slender objects is hurt; (2) IoU can not accurately represent the alignment degree between the receptive field of the feature at the anchor's center and the object.

object-detection Object Detection

Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement

1 code implementation19 Mar 2021 Lijun Gou, Shengkai Wu, Jinrong Yang, Hangcheng Yu, Chenxi Lin, Xiaoping Li, Chao Deng

To solve this problem, a novel image synthesis method is proposed to replace the foreground texture of the source datasets with the texture of the target datasets.

Image Generation object-detection +1

SCD: A Stacked Carton Dataset for Detection and Segmentation

1 code implementation25 Feb 2021 Jinrong Yang, Shengkai Wu, Lijun Gou, Hangcheng Yu, Chenxi Lin, Jiazhuo Wang, Minxuan Li, Xiaoping Li

In this paper, we present a large-scale carton dataset named Stacked Carton Dataset(SCD) with the goal of advancing the state-of-the-art in carton detection.

Instance Segmentation Semantic Segmentation

IoU-aware Single-stage Object Detector for Accurate Localization

2 code implementations12 Dec 2019 Shengkai Wu, Xiaoping Li, Xinggang Wang

The detection confidence is then used as the input of the subsequent NMS and COCO AP computation, which will substantially improve the localization accuracy of models.

General Classification Test

IoU-balanced Loss Functions for Single-stage Object Detection

no code implementations15 Aug 2019 Shengkai Wu, Jinrong Yang, Xinggang Wang, Xiaoping Li

The IoU-balanced localization loss decreases the gradient of examples with low IoU and increases the gradient of examples with high IoU, which can improve the localization accuracy of models.

Classification General Classification +2

A Novel Demodulation and Estimation Algorithm for Blackout Communication: Extract Principal Components with Deep Learning

no code implementations27 May 2019 Haoyan Liu, Yanming Liu, Ming Yang, Xiaoping Li

For reentry or near space communication, owing to the influence of the time-varying plasma sheath channel environment, the received IQ baseband signals are severely rotated on the constellation.

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