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

Showing 261270 of 453 papers

TitleStatusHype
Second-Order Constrained Parametric Proposals and Sequential Search-Based Structured Prediction for Semantic Segmentation in RGB-D Images0
See More for Scene: Pairwise Consistency Learning for Scene Classification0
Self-Supervised In-Domain Representation Learning for Remote Sensing Image Scene Classification0
Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment0
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes0
Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models0
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification0
Shape Distributions of Nonlinear Dynamical Systems for Video-based Inference0
Short-Term Memory Convolutions0
SOAT: A Scene- and Object-Aware Transformer for Vision-and-Language Navigation0
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Benchmark Results

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