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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2951–2975 of 10420 papers

TitleStatusHype
One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection—0
Causal Analysis for Robust Interpretability of Neural Networks—0
Learning More Discriminative Local Descriptors for Few-shot Learning—0
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification—0
Predictive Models from Quantum Computer Benchmarks—0
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks—0
Enhancing Performance of Vision Transformers on Small Datasets through Local Inductive Bias Incorporation—0
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity—0
To transfer or not transfer: Unified transferability metric and analysis—0
Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction—0
Saturated Non-Monotonic Activation Functions—0
Two-in-One: A Model Hijacking Attack Against Text Generation Models—0
Feature Channel Adaptive Enhancement for Fine-Grained Visual Classification—0
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers—0
Meta-Learners for Few-Shot Weakly-Supervised Medical Image SegmentationCode0
Explainable Knowledge Distillation for On-device Chest X-Ray Classification—0
DPMLBench: Holistic Evaluation of Differentially Private Machine LearningCode1
Towards Effective Visual Representations for Partial-Label LearningCode1
A Multi-modal Approach to Single-modal Visual Place Classification—0
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception—0
Learning Semi-supervised Gaussian Mixture Models for Generalized Category DiscoveryCode1
Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classificationCode0
Architectural Vision for Quantum Computing in the Edge-Cloud ContinuumCode0
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide ImagesCode1
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm CorruptionsCode0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified