andreawonderland Goto Github PK
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andreawonderland's Projects
2016cvprcam
Class Activation Mapping
2017iccvgrad-cam
Advanced AI Explainability for computer vision. Support for CNNs and Vision Transformers. Examples and applications for classification, object detection, segmentation, explaining image similarity and more.
amc
awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
bottlenecktransformers
Bottleneck Transformers for Visual Recognition
cifar10
dpt
DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021)
grad-cam.pytorch
pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...
grad-cam_sourcecode_pytorch
[ICCV 2017] Torch code for Grad-CAM
gradcam_tf2
Implementation of GradCAM & Guided GradCAM with Tensorflow 2.x
keras-io
Keras documentation, hosted live at keras.io
pytorch-
《Pytorch模型训练实用教程》中配套代码
relation-aware-global-attention-networks
We design an effective Relation-Aware Global Attention (RGA) module for CNNs to globally infer the attention.
smallsample
vision_transformer
visual-analytics-and-interpretability-in-deep-learning
本项目主要是通过可视分析的手段，对深度学习的可解释性做出讨论与探讨。并且记录小组成员的学习过程与工作
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