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

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Showing 8151–8175 of 10420 papers

TitleStatusHype
DeepAGREL: Biologically plausible deep learning via direct reinforcement—0
AdaScale SGD: A Scale-Invariant Algorithm for Distributed Training—0
Defensive Tensorization: Randomized Tensor Parametrization for Robust Neural Networks—0
Adaptive Data Augmentation with Deep Parallel Generative Models—0
Monte Carlo Deep Neural Network Arithmetic—0
Smart Ternary Quantization—0
Training Data Distribution Search with Ensemble Active Learning—0
Test-Time Training for Out-of-Distribution Generalization—0
Siamese Attention Networks—0
When Robustness Doesn’t Promote Robustness: Synthetic vs. Natural Distribution Shifts on ImageNet—0
Scalable Deep Neural Networks via Low-Rank Matrix Factorization—0
SoftAdam: Unifying SGD and Adam for better stochastic gradient descent—0
Unknown-Aware Deep Neural Network—0
Scale-Equivariant Neural Networks with Decomposed Convolutional Filters—0
Diving into Optimization of Topology in Neural Networks—0
Model-Agnostic Feature Selection with Additional Mutual Information—0
Laconic Image Classification: Human vs. Machine Performance—0
Evo-NAS: Evolutionary-Neural Hybrid Agent for Architecture Search—0
A Kolmogorov Complexity Approach to Generalization in Deep Learning—0
Data Augmentation in Training CNNs: Injecting Noise to Images—0
Distance-based Composable Representations with Neural Networks—0
Learning in Confusion: Batch Active Learning with Noisy Oracle—0
Invariance vs Robustness of Neural Networks—0
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep NetworksCode0
Gated Channel Transformation for Visual RecognitionCode0
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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