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 251–300 of 453 papers

TitleStatusHype
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
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
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
Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching—0
Unsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition—0
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer—0
Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding—0
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding—0
Visually Exploring Multi-Purpose Audio Data—0
Visual Saliency Detection in Advanced Driver Assistance Systems—0
VWise: A novel benchmark for evaluating scene classification for vehicular applications—0
What are You Talking About? Text-to-Image Coreference—0
What is (missing or wrong) in the scene? A Hybrid Deep Boltzmann Machine For Contextualized Scene Modeling—0
What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images—0
Wider or Deeper Neural Network Architecture for Acoustic Scene Classification with Mismatched Recording Devices—0
1-D CNN based Acoustic Scene Classification via Reducing Layer-wise Dimensionality—0
FlexiMo: A Flexible Remote Sensing Foundation Model—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
Harvesting Discriminative Meta Objects with Deep CNN Features for Scene Classification—0
Health Monitoring of Industrial machines using Scene-Aware Threshold Selection—0
Heterogeneous Multi-task Metric Learning across Multiple Domains—0
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks—0
Hierarchical Feature Hashing for Fast Dimensionality Reduction—0
Hierarchical learning for DNN-based acoustic scene classification—0
Hierarchical Metric Learning for Optical Remote Sensing Scene Categorization—0
Hierarchy of Alternating Specialists for Scene Recognition—0
High Order Structure Descriptors for Scene Images—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