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 22262250 of 10420 papers

TitleStatusHype
Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained FeaturesCode1
Differentiable Top-k Classification LearningCode1
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised LearningCode1
FixCaps: An Improved Capsules Network for Diagnosis of Skin CancerCode1
Fixed-point Quantization of Convolutional Neural Networks for Quantized Inference on Embedded PlatformsCode1
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
Distribution Alignment: A Unified Framework for Long-tail Visual RecognitionCode1
EATFormer: Improving Vision Transformer Inspired by Evolutionary AlgorithmCode1
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel SizesCode1
Efficient Attention: Attention with Linear ComplexitiesCode1
FlowNAS: Neural Architecture Search for Optical Flow EstimationCode1
Benchmarking Pathology Feature Extractors for Whole Slide Image ClassificationCode1
Focal and Global Knowledge Distillation for DetectorsCode1
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear MapsCode1
A Call to Reflect on Evaluation Practices for Failure Detection in Image ClassificationCode1
AsymmNet: Towards ultralight convolution neural networks using asymmetrical bottlenecksCode1
FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image RecognitionCode1
Foundation Model Assisted Weakly Supervised Semantic SegmentationCode1
Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image ClassificationCode1
Convolutional Sequence to Sequence LearningCode1
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image ClassificationCode1
Convolutional Spiking Neural Networks for Spatio-Temporal Feature ExtractionCode1
Convolutional Xformers for VisionCode1
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic SparsityCode1
Open-World Semi-Supervised LearningCode1
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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