YOLO有效涨点改进永久更新,学习改进过程中包括答疑解惑,助力高效发论文。DCNv4可变性卷积 | CVPR 2024 | YOLO改进 | DCNv4即插即用模块,适用于图像分类,目标检测,图像分割,图像生成等所有CV任务通用模块, 视频播放量 2129、弹幕量 2、点赞数 38、投硬币枚数 18、收藏人
代码:https://github.com/OpenGVLab/DCNv4 论文:https://arxiv.org/abs/2401.06197 CVPR 2024 论文和开源项目合集请戳—>https://github.com/amusi/CVPR2024-Papers-with-Code 本文强势推出 Deformable Convolution v4 (DCNv4),这是一种专为广泛的视觉应用而设计的高效且有效的动态和稀疏的算子。 DCNv4 通过两...
https://arxiv.org/pdf/2401.06197.pdf https://github.com/OpenGVLab/DCNv4 本文介绍了一种高效和有效的算子DCNv 4,它是专为广泛的视觉应用而设计的。与其前身DCNv 3相比,DCNv 4有两个关键增强功能:(1)去除空间聚合中的softmax归一化,以增强其动态性和表达能力;(2)优化存储器访问以最小化冗余操作以加速。
Jan 15, 2024: 🚀 "DCNv4" is released! Introduction We introduce Deformable Convolution v4 (DCNv4), a highly efficient and effective operator designed for a broad spectrum of vision applications. DCNv4 addresses the limitations of its predecessor, DCNv3, with two key enhancements: 1. removing...
[CVPR 2024] Deformable Convolution v4. Contribute to tlwzzy/DCNv4 development by creating an account on GitHub.
[CVPR 2024] Deformable Convolution v4. Contribute to OpenGVLab/DCNv4 development by creating an account on GitHub.