EleanorTT's repositories
daod
域适应目标检测
XAI
可解释性人工智能-深度学习
IBN-Net
Instance-Batch Normalization Networks (ECCV2018)
mmdetection
OpenMMLab Detection Toolbox and Benchmark
ultralytics-face
WIDER-FACE Face Detector Based On YOLOV8
cross-domain-detection
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation [Inoue+, CVPR2018].
FINet-SFID_datasets
Foggy Insulator Network, Dataset and Code. Improved object detection network, synthetic fog, data augmentation, channel attention mechanism. Insulator & defect detection
Efficient-Computing
Efficient computing methods developed by Huawei Noah's Ark Lab
mmyolo-asff
OpenMMLab YOLO series toolbox and benchmark
cycle-confusion
Code and models for ICCV2021 paper "Robust Object Detection via Instance-Level Temporal Cycle Confusion".
transferlearning-DeepDA
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
dino
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
dinov2
PyTorch code and models for the DINOv2 self-supervised learning method.
DINO-VLPart
[ICCV2023] VLPart: Going Denser with Open-Vocabulary Part Segmentation
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
Sparse-Sharpness-Aware-Minimization
[NeurIPS 2022] Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach -- Official Implementation
mrs_uav_system
The entry point to the MRS UAV system.
dimensionality_reduction
特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现
d2l-zh
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被60多个国家的400多所大学用于教学。
lucid
A collection of infrastructure and tools for research in neural network interpretability.
fedsam
模型泛化-论文无,代码可看
EESRGAN
Small-Object Detection in Remote Sensing (satellite) Images with End-to-End Edge-Enhanced GAN and Object Detector Network
nimbro_network
ROS network stack: Topic/service transport over unreliable network connections
mmpose
OpenMMLab Pose Estimation Toolbox and Benchmark.