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 76–100 of 453 papers

TitleStatusHype
Minimizing Risk Through Minimizing Model-Data Interaction: A Protocol For Relying on Proxy Tasks When Designing Child Sexual Abuse Imagery Detection Models—0
Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 ChallengeCode0
FrogDogNet: Fourier frequency Retained visual prompt Output Guidance for Domain Generalization of CLIP in Remote SensingCode0
FlexiMo: A Flexible Remote Sensing Foundation Model—0
Open-Vocabulary Semantic Segmentation with Uncertainty Alignment for Robotic Scene Understanding in Indoor Building Environments—0
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 Images—0
Improving Acoustic Scene Classification with City Features—0
Optimal Transport Adapter Tuning for Bridging Modality Gaps in Few-Shot Remote Sensing Scene Classification—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery—0
Creating a Good Teacher for Knowledge Distillation in Acoustic Scene Classification—0
Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification—0
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer—0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features—0
Quantum-Enhanced Transformers for Robust Acoustic Scene Classification in IoT Environments—0
Multi-Label Scene Classification in Remote Sensing Benefits from Image Super-Resolution—0
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding—0
Enhancing Scene Classification in Cloudy Image Scenarios: A Collaborative Transfer Method with Information Regulation Mechanism using Optical Cloud-Covered and SAR Remote Sensing ImagesCode0
FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models—0
Improving Acoustic Scene Classification in Low-Resource Conditions—0
UniRS: Unifying Multi-temporal Remote Sensing Tasks through Vision Language ModelsCode0
How Certain are Uncertainty Estimates? Three Novel Earth Observation Datasets for Benchmarking Uncertainty Quantification in Machine Learning—0
Multimodal Remote Sensing Scene Classification Using VLMs and Dual-Cross Attention NetworksCode0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—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