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

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Showing 241–250 of 453 papers

TitleStatusHype
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
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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