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 251–275 of 453 papers

TitleStatusHype
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes—0
Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models—0
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification—0
Shape Distributions of Nonlinear Dynamical Systems for Video-based Inference—0
Short-Term Memory Convolutions—0
SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation—0
Solving Visual Madlibs with Multiple Cues—0
Sparse Output Coding for Large-Scale Visual Recognition—0
Spatio-Temporal Attention Pooling for Audio Scene Classification—0
SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification—0
Squeeze-Excitation Convolutional Recurrent Neural Networks for Audio-Visual Scene Classification—0
Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 1 Theory—0
Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 2 Validation—0
Task 1A DCASE 2021: Acoustic Scene Classification with mismatch-devices using squeeze-excitation technique and low-complexity constraint—0
Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems—0
TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correction—0
The 2017 DAVIS Challenge on Video Object Segmentation—0
TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning—0
Towards Robust Domain Generalization in 2D Neural Audio Processing—0
Towards Scalable and Generalizable Earth Observation Data Mining via Foundation Model Composition—0
Traffic scene recognition based on deep cnn and vlad spatial pyramids—0
Joint Spatial and Layer Attention for Convolutional Networks—0
Understanding Indoor Scenes Using 3D Geometric Phrases—0
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks—0
Unlocking the capabilities of explainable fewshot learning in remote sensing—0
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All datasetsUC Merced Land Use DatasetPlaces365-Standard

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