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 301–350 of 453 papers

TitleStatusHype
Cross-task pre-training for on-device acoustic scene classification—0
Acoustic Scene Classification Based on a Large-margin Factorized CNN—0
Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification—0
Acoustic scene analysis with multi-head attention networksCode0
Receptive-field-regularized CNN variants for acoustic scene classificationCode1
Semantic-Aware Scene RecognitionCode0
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene ClassificationCode0
Online Sensor Hallucination via Knowledge Distillation for Multimodal Image Classification—0
Multiple instance dense connected convolution neural network for aerial image scene classification—0
Scene Classification in Indoor Environments for Robots using Context Based Word Embeddings—0
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning—0
City classification from multiple real-world sound scenesCode0
Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling—0
Acoustic Scene Classification Using Fusion of Attentive Convolutional Neural Networks for DCASE2019 Challenge—0
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene ClassificationCode1
Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial VehiclesCode1
SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data FusionCode1
CNN depth analysis with different channel inputs for Acoustic Scene Classification—0
Few-Shot Learning with Per-Sample Rich Supervision—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Dynamic Traffic Scene Classification with Space-Time Coherence—0
Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes—0
Unsupervised Adversarial Domain Adaptation Based On The Wasserstein Distance For Acoustic Scene ClassificationCode0
Deep CNNs Meet Global Covariance Pooling: Better Representation and GeneralizationCode1
Acoustic Scene Classification by Implicitly Identifying Distinct Sound EventsCode0
Heterogeneous Multi-task Metric Learning across Multiple Domains—0
Spatio-Temporal Attention Pooling for Audio Scene Classification—0
Equivariant Multi-View NetworksCode0
Rotated Feature Network for multi-orientation object detection—0
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach—0
Understanding and Visualizing Deep Visual Saliency ModelsCode0
Deep Discriminative Representation Learning with Attention Map for Scene Classification—0
BigEarthNet: A Large-Scale Benchmark Archive For Remote Sensing Image Understanding—0
Joint Spatial and Layer Attention for Convolutional Networks—0
Enhancing Sound Texture in CNN-Based Acoustic Scene Classification—0
A Remote Sensing Image Dataset for Cloud RemovalCode0
Artistic Object Recognition by Unsupervised Style Adaptation—0
Revisiting Multi-Task Learning with ROCK: a Deep Residual Auxiliary Block for Visual DetectionCode0
Scene Categorization from Contours: Medial Axis Based Salience Measures—0
Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene?—0
Training neural audio classifiers with few dataCode0
Deep Within-Class Covariance Analysis for Robust Deep Audio Representation Learning—0
SiftingGAN: Generating and Sifting Labeled Samples to Improve the Remote Sensing Image Scene Classification Baseline in vitroCode0
CNNs for Surveillance Footage Scene Classification—0
CNNs-based Acoustic Scene Classification using Multi-Spectrogram Fusion and Label Expansions—0
Geolocation Estimation of Photos using a Hierarchical Model and Scene ClassificationCode0
Hierarchy of Alternating Specialists for Scene Recognition—0
Unsupervised adversarial domain adaptation for acoustic scene classificationCode0
Acoustic Scene Classification: A Competition Review—0
A multi-device dataset for urban acoustic scene classificationCode0
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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