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Odyssey: Empowering Agents with Open-World Skills
From Handcrafted to Deep Features for Pedestrian Detection: A Survey (TPAMI 2021)
[ICLR'24] Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
This is the official repository for our recent work: PIDNet
一款基于Netty Zookeeper Spring实现的轻量级Java RPC框架。提供服务注册，发现，负载均衡，支持API调用，Spring集成和Spring Boot starter使用。是一个学习RPC工作原理的良好示例。
DeepLab v3 model in PyTorch. Support different backbones.
Real-time High-Resolution Neural Network with Semantic Guidance for Crack Segmentation
[ECCV W 2022] "CrackSeg9k: A Collection and Benchmark for Crack Segmentation Datasets and Frameworks" by Shreyas Kulkarni, Shreyas Singh, Dhananjay Balakrishnan, Siddharth Sharma, Saipraneeth Devun…
一些关于目标检测的脚本的改进思路代码，详细请看readme.md
A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
A lightweight CNN-based model for medical image segmentation.
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)
Pretrained DeepLabv3 and DeepLabv3 for Pascal VOC & Cityscapes
Light-Weight RefineNet for Real-Time Semantic Segmentation
reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
Semantic segmentation models with 500 pretrained convolutional and transformer-based backbones.
[CVPR 2020] CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement
We developed a python UI based on labelme and segment-anything for pixel-level annotation. It support multiple masks generation by SAM(box/point prompt), efficient polygon modification and category…
🎨 Semantic segmentation models, datasets and losses implemented in PyTorch.
EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation
🔥 💪 Crack-Detection-and-Segmentation-Dataset-for-UAV-Inspection
DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
A Pytorch implementation of DeepCrack and RoadNet projects.
This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu