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 3126–3150 of 10420 papers

TitleStatusHype
Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation—0
Discovering Parametric Activation Functions—0
Robust Multi-instance Learning with Stable Instances—0
Discovering Influential Neuron Path in Vision Transformers—0
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations—0
Distribution-Aware Adaptive Multi-Bit Quantization—0
Distribution Learning Based on Evolutionary Algorithm Assisted Deep Neural Networks for Imbalanced Image Classification—0
Distribution-sensitive Information Retention for Accurate Binary Neural Network—0
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training—0
Addressing Imbalance for Class Incremental Learning in Medical Image Classification—0
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models—0
Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification—0
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning—0
Discovering Discriminative Cell Attributes for HEp-2 Specimen Image Classification—0
Divergent Search for Few-Shot Image Classification—0
Generating Hard Examples for Pixel-wise Classification—0
Diverse Feature Learning by Self-distillation and Reset—0
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks—0
Bombus Species Image Classification—0
DISCO: Distributed Inference with Sparse Communications—0
Block-wise Scrambled Image Recognition Using Adaptation Network—0
Diversifying Sample Generation for Accurate Data-Free Quantization—0
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Diversity Matters When Learning From Ensembles—0
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency—0
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified