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

November 15, 2023

Domain Aligned CLIP for Few-shot Classification
Muhammad Waleed Gondal, Jochen Gast, Inigo Alonso Ruiz, Richard Droste, Tommaso Macri, Suren Kumar, Luitpold Staudigl
Single CLIP Shot Classification Cross Modal Alignment Internet Service Domain Efficient Domain Adaptation 2 Dimensional Vision Language Model

November 14, 2023

Dual-channel Prototype Network for few-shot Classification of Pathological Images
Hao Quan, Xinjia Li, Dayu Hu, Tianhang Nan, Xiaoyu Cui
Image Classification Shot Classification Pathology Image Pathological Feature Pathological Image

November 4, 2023

Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification
Hao Zheng, Runqi Wang, Jianzhuang Liu, Asako Kanezaki
Knowledge Distillation Classification Code Domain Shift Shot Classification Feature Denoising Joint Distillation

October 21, 2023

Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models
Pierre Colombo, Victor Pellegrain, Malik Boudiaf, Victor Storchan, Myriam Tami, Ismail Ben Ayed, Celine Hudelot, Pablo Piantanida
Natural Language Processing Classification Code Text Modality Shot Classification NLP Community Gradient Regularization Transductive Learning Transductive Inference

October 19, 2023

Label-Aware Automatic Verbalizer for Few-Shot Text Classification
Thanakorn Thaminkaew, Piyawat Lertvittayakumjorn, Peerapon Vateekul
Language Model Text Classification Shot Classification Prompt Based Learning Shot Text Classification Automatic Verbalizer

October 16, 2023

Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
Tianjun Ke, Haoqun Cao, Zenan Ling, Feng Zhou
Classification Code Meta Learning Shot Classification Softmax Gating

October 7, 2023

PatchProto Networks for Few-shot Visual Anomaly Classification
Jian Wang, Yue Zhuo
Shot Learning Shot Classification Shot Anomaly Detection

October 5, 2023

PrototypeFormer: Learning to Explore Prototype Relationships for Few-shot Image Classification
Feihong He, Gang Li, Lingyu Si, Leilei Yan, Fanzhang Li, Fuchun Sun
Shot Classification Shot Image Classification

September 28, 2023

Logarithm-transform aided Gaussian Sampling for Few-Shot Learning
Vaibhav Ganatra
LeArning Abstract Shot Classification Gaussian Distribution Shot Image Classification Discrete Logarithm Gaussian Sampling

September 23, 2023

HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues
Ankit Jha, Debabrata Pal, Mainak Singha, Naman Agarwal, Biplab Banerjee
Classification Code Meta Learning Audio Visual Multimodal Information Shot Classification Unimodal Representation

September 18, 2023

Hyperbolic vs Euclidean Embeddings in Few-Shot Learning: Two Sides of the Same Coin
Gabriel Moreira, Manuel Marques, João Paulo Costeira, Alexander Hauptmann
LeArning Abstract Representation Learning Shot Classification Hyperbolic Space Spatial Encoder Hyperbolic Embeddings Hyperbolic Neural Network Euclidean Embeddings

September 4, 2023

Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification
Marzi Heidari, Abdullah Alchihabi, Qing En, Yuhong Guo
Classification Code Shot Classification Prototype Learning Domain Few Shot

August 8, 2023

Few-shot medical image classification with simple shape and texture text descriptors using vision-language models
Michal Byra, Muhammad Febrian Rachmadi, Henrik Skibbe
Vision Language Model Image Classification Medical Image Medical Image Analysis Object Shape Shot Classification Texture Recognition

August 1, 2023

Adaptive Semantic Consistency for Cross-domain Few-shot Classification
Hengchu Lu, Yuanjie Shao, Xiang Wang, Changxin Gao
Shot Classification Consistency Regularization Semantic Consistency Cross Domain Robustness Domain Few Shot Generic Few Shot Training Data

July 26, 2023

ECO: Ensembling Context Optimization for Vision-Language Models
Lorenzo Agnolucci, Alberto Baldrati, Francesco Todino, Federico Becattini, Marco Bertini, Alberto Del Bimbo
Vision Language Model Image Classification Shot Classification Zero Shot Transfer Context Optimization

July 6, 2023

Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
Jishnu Jaykumar P, Kamalesh Palanisamy, Yu-Wei Chao, Xinya Du, Yu Xiang
LeArning Abstract Shot Learning Shot Classification Shot Example Unimodal Representation

July 4, 2023

LPN: Language-guided Prototypical Network for few-shot classification
Kaihui Cheng, Chule Yang, Xiao Liu, Naiyang Guan, Zhiyuan Wang
Multimodal Information Shot Classification Class Relevant

June 4, 2023

Retrieval-Enhanced Visual Prompt Learning for Few-shot Classification
Jintao Rong, Hao Chen, Linlin Ou, Tianxiao Chen, Xinyi Yu, Yifan Liu
Large Vision Language Model Prompt Learning Shot Classification Retrieval Enhanced

June 2, 2023

LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa
Distribution Detection Prompt Learning Distribution Generalization Shot Classification Shot Out of Distribution Detection Distribution Benchmark

May 30, 2023

SENet: A Spectral Filtering Approach to Represent Exemplars for Few-shot Learning
Tao Zhang, Wu Huang
Shot Learning Shot Classification Exemplar Image Exemplar Guided Prototype Aggregation Kernel Induced Loss