SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Showing 301310 of 10419 papers

TitleStatusHype
Falcon: A Remote Sensing Vision-Language Foundation ModelCode3
Open-Set Plankton Recognition0
Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images0
A Multi-Modal Federated Learning Framework for Remote Sensing Image Classification0
(, δ) Considered Harmful: Best Practices for Reporting Differential Privacy GuaranteesCode0
Interpretable Image Classification via Non-parametric Part Prototype LearningCode1
Multiplicative Learning0
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild0
Learning Interpretable Logic Rules from Deep Vision Models0
Extreme Learning Machines for Attention-based Multiple Instance Learning in Whole-Slide Image Classification0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified