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 8190 of 453 papers

TitleStatusHype
Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image EncodersCode0
What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images0
Improving Acoustic Scene Classification with City Features0
Optimal Transport Adapter Tuning for Bridging Modality Gaps in Few-Shot Remote Sensing Scene Classification0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing0
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification0
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification0
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features0
Show:102550
← PrevPage 9 of 46Next →

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