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BT 反吸血工具 - 自动封禁不受欢迎、吸血和异常的 BT 客户端，并支持自定义规则。PeerId黑名单/UserAgent黑名单/IP CIDR/假进度/超量下载/进度回退/多播追猎/连锁封禁/伪装检测 支持 qBittorrent/Transmission/Deluge/BiglyBT/Vuze(Azureus)/BitComet
When do we not need larger vision models?
Official implementation of "Towards Efficient Visual Adaption via Structural Re-parameterization".
[TPAMI] Searching prompt modules for parameter-efficient transfer learning.
[ICCV 2023 & AAAI 2023] Binary Adapters & FacT, [Tech report] Convpass
[ECCV 2024] Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning
A method to increase the speed and lower the memory footprint of existing vision transformers.
(ARXIV24) This is the official code repository for "VM-UNet: Vision Mamba UNet for Medical Image Segmentation".
VMamba: Visual State Space Models，code is based on mamba
A global resource download orchestration system, build your home download center.
Customize processors and process resource downloads to support any resource, plug-in and component-based development.
This is the repo for our new project Highly Accurate Dichotomous Image Segmentation
Official code of Remote Sensing Mamba
[arXiv] The official code for "UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation".
(CVPR2024)RMT: Retentive Networks Meet Vision Transformer
This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
[ECCVW 2022] The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"
SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process
[CVPR 2023] Token Contrast for Weakly-Supervised Semantic Segmentation
BinaryViT: Pushing Binary Vision Transformers Towards Convolutional Models
Unofficial implementation of LSQ-Net, a neural network quantization framework
阅读3服务器版，桌面端，iOS可用。后端 Kotlin + Spring Boot + Vert.x + Coroutine ；前端 Vue.js + Element。麻烦点点star，关注一下公众号【假装大佬】❗️ Demo服务器由于未备案已被关停，建议自行搭建
The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].
ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting (ICCV 2021)