Shot Classification

Shot classification, particularly few-shot classification, focuses on training classifiers with limited labeled data, aiming to improve generalization to unseen classes. Current research emphasizes adapting pre-trained models like CLIP, employing meta-learning algorithms, and exploring techniques such as prompt engineering and hyperdimensional computing to enhance efficiency and accuracy. This field is crucial for addressing data scarcity issues in various domains, including medical imaging and natural language processing, enabling the development of more robust and adaptable AI systems.

Papers

April 5, 2022

MetaAudio: A Few-Shot Audio Classification Benchmark
Calum Heggan, Sam Budgett, Timothy Hospedales, Mehrdad Yaghoobi
Shot Learning Shot Classification Audio Datasets Acoustic Domain Shot Class Incremental Audio Classification Audio Classification Benchmark

April 1, 2022

Selecting task with optimal transport self-supervised learning for few-shot classification
Renjie Xu, Xinghao Yang, Baodi Liu, Kai Zhang, Weifeng Liu
Self Supervised Learning Optimal Transport Shot Classification Self Supervised Training Task Similarity Training Task Task Selection

March 30, 2022

Overcoming challenges in leveraging GANs for few-shot data augmentation
Christopher Beckham, Issam Laradji, Pau Rodriguez, David Vazquez, Derek Nowrouzezahrai, Christopher Pal
Generative Model Technical Challenge Shot Learning GAN Model Shot Classification

March 29, 2022

March 25, 2022

CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification
Philip Chikontwe, Soopil Kim, Sang Hyun Park
Classification Code Self Attention Shot Classification Discriminative Feature Attention Score Metric Based Meta Learning

February 18, 2022

Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning
Jiawei Yang, Hanbo Chen, Jiangpeng Yan, Xiaoyu Chen, Jianhua Yao
Contrastive Learning Shot Learning Shot Classification Image Analysis Deep Understanding Better Generalization Histology Image Space Augmentation

February 17, 2022

Semantically Proportional Patchmix for Few-Shot Learning
Jingquan Wang, Jing Xu, Yu Pan, Zenglin Xu
LeArning Abstract Transfer Learning Shot Learning Shot Classification Training Image Cross Modal Manifold CutMix

February 8, 2022

Spectral Propagation Graph Network for Few-shot Time Series Classification
Ling Yang, Shenda Hong, Luxia Zhang
Shot Classification Spectral Diffusion Structure Spectrum Relationship

February 5, 2022

Few-shot Learning as Cluster-induced Voronoi Diagrams: A Geometric Approach
Chunwei Ma, Ziyun Huang, Mingchen Gao, Jinhui Xu
Shot Learning Shot Classification Geometric Approach Voronoi Diagram Structural Heterogeneity

January 30, 2022

PLATINUM: Semi-Supervised Model Agnostic Meta-Learning using Submodular Mutual Information
Changbin Li, Suraj Kothawade, Feng Chen, Rishabh Iyer
Meta Learning Shot Classification Striking GOld Agnostic Meta learnIng Submodular Mutual Information Agnostic Meta Learning

January 7, 2022

Budget-aware Few-shot Learning via Graph Convolutional Network
Shipeng Yan, Songyang Zhang, Xuming He
Shot Learning Graph Convolutional Network Shot Classification Efficient Few Shot Learning

December 27, 2021

Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains
Yuan-Chia Cheng, Ci-Siang Lin, Fu-En Yang, Yu-Chiang Frank Wang
Classification Code Shot Learning Meta Learning Shot Classification Unseen Domain Domain Invariant Feature New Learning

December 14, 2021

Exploring Category-correlated Feature for Few-shot Image Classification
Jing Xu, Xinglin Pan, Xu Luo, Wenjie Pei, Zenglin Xu
Shot Classification Shot Image Classification Biased Feature Categorical Feature Image Rectification

December 7, 2021

Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
Rongkai Ma, Pengfei Fang, Gil Avraham, Yan Zuo, Tianyu Zhu, Tom Drummond, Mehrtash Harandi
Deep Convolutional Neural Network Shot Classification Shot Detection Shot Classification Benchmark

December 6, 2021

November 9, 2021

Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation
Minyoung Kim, Timothy Hospedales
Gaussian Process Posterior Inference Shot Classification Meta Training Laplace Approximation