kongbia's repositories
CVPR2022-Paper-Code-Interpretation
cvpr2019 papers
Single_Object_Tracking_Paper_List
Paper list for single object tracking
kongbia.github.io
个人博客 hexo
Algorithms_Engineer_Interview
计算机视觉算法工程师实习生面试总结（微软、阿里、商汤、海康、华为、平安offer）
awesome-multiple-object-tracking
Resources for Multiple Object Tracking (MOT)
Comparison
Compare performances of algorithms on Objcet Tracking Benchmarks (SOT/MOT...)
darknet
Convolutional Neural Networks
GlobalTrack
Official PyTorch implementation of "GlobalTrack: A Simple and Strong Baseline for Long-term Tracking" @ AAAI2020.
ICCV2021-Paper-Code-Interpretation
ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理
LeetcodeTop
汇总各大互联网公司容易考察的高频leetcode题🔥
LSOTB-TIR
LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark (ACM MM2020)
maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
OSTrack
[ECCV 2022] Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
pytorch-classification
Config File is All You Need: An Image Classification Codebase Written in PyTorch
pytorch-ssd
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.
PyTorch_YOLOv4
PyTorch implementation of YOLOv4
SiamDW
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
SmallObjectDetectionList
List of the Papers Addressing Vision-based Small Object Detection
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Transformer_Tracking
This repository is a paper digest of Transformer-related approaches in visual tracking tasks.
TransT
Transformer Tracking (CVPR2021)
Yolo_Label
GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2 https://github.com/AlexeyAB/darknet, https://github.com/pjreddie/darknet
YOLOv3-model-pruning
对 YOLOv3 做模型剪枝（network slimming），对于 oxford hand 数据集（因项目需要），模型剪枝后的参数量减少 80%，Infer 的速度达到原来 2 倍，mAP 基本不变