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
Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network—0
Satellite Image Scene Classification via ConvNet with Context Aggregation—0
Scalable Multitask Representation Learning for Scene Classification—0
Scenarios: A New Representation for Complex Scene Understanding—0
Scene Categorization from Contours: Medial Axis Based Salience Measures—0
Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings—0
Scene Classification With Semantic Fisher Vectors—0
Scene Recognition with Objectness, Attribute and Category Learning—0
Scene Retrieval for Contextual Visual Mapping—0
SeasoNet: A Seasonal Scene Classification, segmentation and Retrieval dataset for satellite Imagery over Germany—0
Second-Order Constrained Parametric Proposals and Sequential Search-Based Structured Prediction for Semantic Segmentation in RGB-D Images—0
See More for Scene: Pairwise Consistency Learning for Scene Classification—0
Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classification—0
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment—0
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
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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