VIP cheatsheets for Stanford's CS 230 Deep Learning

Code for the experiments of the ICML 2021 Interpretability workshop paper "This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks"

Learning Bottleneck Concepts in Image Classification (CVPR 2023)

This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaof…

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

Code for "Interpretable image classification with differentiable prototypes assignment", ECCV 2022

Official PyTorch Repository of "Task Discrepancy Maximization for Fine-grained Few-Shot Classification" (TDM, CVPR 2022 Oral Paper)

[ICCV'21] Official PyTorch implementation of Relational Embedding for Few-Shot Classification

Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

[ECCV2022] PyTorch re-implementation of Self-Supervision Can Be a Good Few-Shot Learner

This is a PyTorch implementation of the paper "Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization (MMAL-Net)" (Fan Zhang, Meng Li, Guisheng Zhai, Yizhao Liu).

Code for our CVPR2021 paper coordinate attention

Dual Attention Network for Scene Segmentation (CVPR2019)

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

Summary of related papers on visual attention. Related code will be released based on Jittor gradually.

[ICML 2023] A Closer Look at Few-shot Classification Again

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

Leaderboards for few-shot image classification on miniImageNet, tieredImageNet, FC100, and CIFAR-FS.

multi instance attention network for few-shot learning

[PR22, Highly Cited Paper] Learning Attention-Guided Pyramidal Features for Few-shot Fine-grained Recognition

(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks

The summary of code and paper for few-shot learning in fine-grained recognition

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

Implementation of Zero-Shot Learning algorithm using Word2Vecs as class embeddings