no code implementations • 1 Apr 2024 • Hongwei Zheng, Linyuan Zhou, Han Li, Jinming Su, Xiaoming Wei, Xiaoming Xu
To this end, this paper introduces the Balanced and Entropy-based Mix (BEM), a pioneering mixing approach to re-balance the class distribution of both data quantity and uncertainty.
1 code implementation • 1 Feb 2023 • Kaiheng Weng, Xiangxiang Chu, Xiaoming Xu, Junshi Huang, Xiaoming Wei
Thus, how to design a neural network to efficiently use the computing ability and memory bandwidth of hardware is a critical problem.
5 code implementations • 13 Jan 2023 • Chuyi Li, Lulu Li, Yifei Geng, Hongliang Jiang, Meng Cheng, Bo Zhang, Zaidan Ke, Xiaoming Xu, Xiangxiang Chu
For a glimpse of performance, our YOLOv6-N hits 37. 5% AP on the COCO dataset at a throughput of 1187 FPS tested with an NVIDIA Tesla T4 GPU.
Ranked #1 on Real-Time Object Detection on MS COCO
no code implementations • 4 Jan 2023 • Haojie Yu, Kang Zhao, Xiaoming Xu
To alleviate this issue, inspired by masked autoencoder (MAE), which is a data-efficient self-supervised learner, we propose Semi-MAE, a pure ViT-based SSL framework consisting of a parallel MAE branch to assist the visual representation learning and make the pseudo labels more accurate.
7 code implementations • 7 Sep 2022 • Chuyi Li, Lulu Li, Hongliang Jiang, Kaiheng Weng, Yifei Geng, Liang Li, Zaidan Ke, Qingyuan Li, Meng Cheng, Weiqiang Nie, Yiduo Li, Bo Zhang, Yufei Liang, Linyuan Zhou, Xiaoming Xu, Xiangxiang Chu, Xiaoming Wei, Xiaolin Wei
The YOLO community has prospered overwhelmingly to enrich its use in a multitude of hardware platforms and abundant scenarios.
Ranked #14 on Object Detection on COCO-O