SOTAVerified

Scene Classification

Scene Classification is a task in which scenes from photographs are categorically classified. Unlike object classification, which focuses on classifying prominent objects in the foreground, Scene Classification uses the layout of objects within the scene, in addition to the ambient context, for classification.

Source: Scene classification with Convolutional Neural Networks

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–425 of 453 papers

TitleStatusHype
What makes ImageNet good for transfer learning?Code0
AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene ClassificationCode1
Solving Visual Madlibs with Multiple Cues—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
An ensemble learning method for scene classification based on Hidden Markov Model image representation—0
Collaborative Layer-wise Discriminative Learning in Deep Neural Networks—0
Hierarchical learning for DNN-based acoustic scene classification—0
Classifying Variable-Length Audio Files with All-Convolutional Networks and Masked Global PoolingCode0
Adversarial Training For Sketch Retrieval—0
Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classificationCode0
Label Tree Embeddings for Acoustic Scene Classification—0
Modality and Component Aware Feature Fusion For RGB-D Scene Classification—0
Towards Better Exploiting Convolutional Neural Networks for Remote Sensing Scene ClassificationCode0
Shape Distributions of Nonlinear Dynamical Systems for Video-based Inference—0
Relay Backpropagation for Effective Learning of Deep Convolutional Neural NetworksCode0
Per-Sample Kernel Adaptation for Visual Recognition and Grouping—0
Harvesting Discriminative Meta Objects with Deep CNN Features for Scene Classification—0
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks—0
Histogram of gradients of Time-Frequency Representations for Audio scene detection—0
A Spatial Layout and Scale Invariant Feature Representation for Indoor Scene Classification—0
A Discriminative Representation of Convolutional Features for Indoor Scene Recognition—0
Reflection Invariance: an important consideration of image orientation—0
Learning Coarse-to-Fine Sparselets for Efficient Object Detection and Scene Classification—0
Scene Classification With Semantic Fisher Vectors—0
Second-Order Constrained Parametric Proposals and Sequential Search-Based Structured Prediction for Semantic Segmentation in RGB-D Images—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1µ2Net+ (ViT-L/16)Accuracy (%)100—Unverified
2AGOSAccuracy (%)99.88—Unverified
3LSE-NetAccuracy (%)99.78—Unverified
4ResNet50Accuracy (%)99.61—Unverified
5MSMatchAccuracy (%)98.33—Unverified
6MIDC-NetAccuracy (%)97.4—Unverified
#ModelMetricClaimedVerifiedStatus
1iSQRT-COV-Net (ResNet-50)Top 1 Error43.68—Unverified
2WaveMixTop 1 Error43.55—Unverified