Browse State-of-the-Art › Scene Classification
Scene Classification
148 papers with code · 2 benchmarks · 23 datasets archive 2025-07-28
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
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| UC Merced Land Use Dataset (6 rows) | µ2Net+ (ViT-L/16) | A Continual Development Methodology for Large-scale Multitask... | code | — | Compare |
| Places365-Standard (2 rows) | WaveMix | WaveMix: A Resource-efficient Neural Network for Image Analysis | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
23 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 148 papers with code (453 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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18 May 2020 4 repositories listedBesides, we present an RSI scene classification dataset named as CSU-RSISC10 dataset to preserve the spatial information between scenes in a new way of organization.
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1 Mar 2017 4 repositories listedDuring the past years, significant efforts have been made to develop various datasets or present a variety of approaches for scene classification from remote sensing images.
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28 Mar 2024 3 repositories listed Syntology ran 8 of 10 samples · 2 unverifiedRemote sensing image classification forms the foundation of various understanding tasks, serving a crucial function in remote sensing image interpretation.
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9 May 2023 3 repositories listedExisting AI-related research in remote sensing primarily focuses on visual understanding tasks while neglecting the semantic understanding of the objects and their relationships.
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8 Oct 2021 3 repositories listedConcretely, the MTLN consists of a shared branch for all tasks and multiple task-specific branches with each for one task.
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31 Aug 2020 3 repositories listedFinally, we demonstrate that the use of spatial and temporal attention layers improves our model's performance by 2.
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3 Jul 2019 3 repositories listedTo this end, we analyse the receptive field (RF) of these CNNs and demonstrate the importance of the RF to the generalization capability of the models.
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18 Jun 2019 3 repositories listedThe availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from multi-sensor remote sensing imagery.
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15 Apr 2019 3 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 3 pointer-only (licence)The proposed methods are highly modular, readily plugged into existing deep CNNs.
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1 Jul 2016 3 repositories listedWe present a novel technique to automatically colorize grayscale images that combines both global priors and local image features.
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29 Mar 2024 2 repositories listed Syntology ran 2 of 4 samples · 2 unverifiedVHM is built on a large-scale remote sensing image-text dataset with rich-content captions (VersaD), and an honest instruction dataset comprising both factual and deceptive questions (HnstD).
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20 Mar 2024 2 repositories listed Syntology ran 4 of 5 samples · 1 unverifiedHowever, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks.
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7 Feb 2024 2 repositories listedPreviously, we developed a Multiple Instance Multi-Resolution Fusion (MIMRF) framework that addresses label uncertainty for fusion, but it can be slow to train due to the large search space for the fuzzy measures used…
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11 Sep 2023 2 repositories listed Syntology ran 6 of 7 samples · 1 unverifiedThe increasing availability of multi-sensor data sparks wide interest in multimodal self-supervised learning.
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8 Jun 2023 2 repositories listedHowever, we show that the dual CNN-based encoder of EMSANet can be replaced with a single Transformer-based encoder.
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10 Jul 2022 2 repositories listedIn order to evaluate our multi-task approach, we extend the annotations of the common RGB-D indoor datasets NYUv2 and SUNRGB-D for instance segmentation and orientation estimation.
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15 Feb 2022 2 repositories listedYet these datasets are time-consuming and labor-exhaustive to obtain on realistic tasks.
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18 Jun 2021 2 repositories listedThe paper further evaluates the performance of the Multi-Net and the efficiency of the developed system.
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10 Sep 2020 2 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)Second, we use a similar analytic method to analyze a generative adversarial network (GAN) model trained to generate scenes.
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14 Jun 2020 2 repositories listed Syntology ran 4 of 9 samples · 5 unverifiedThe primary model has a foveated-textural input stage, which we compare to a model with foveated-blurred input and a model with spatially-uniform blurred input (both matched for perceptual compression), and a final…
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5 Sep 2019 2 repositories listedOne side effect of restricting the RF of CNNs is that more frequency information is lost.
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20 Jun 2019 2 repositories listedUnmanned Aerial Vehicles (UAVs), equipped with camera sensors can facilitate enhanced situational awareness for many emergency response and disaster management applications since they are capable of operating in remote…
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3 Jan 2019 2 repositories listedRemoving clouds is an indispensable pre-processing step in remote sensing image analysis.
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24 Oct 2018 2 repositories listedWe investigate supervised learning strategies that improve the training of neural network audio classifiers on small annotated collections.
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25 Jul 2018 2 repositories listed Syntology ran 1 of 2 samples · 1 unverifiedThis paper introduces the acoustic scene classification task of DCASE 2018 Challenge and the TUT Urban Acoustic Scenes 2018 dataset provided for the task, and evaluates the performance of a baseline system in the task.
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19 Jun 2018 2 repositories listedIn this paper, we propose a system that consists of a simple fusion of two methods of the aforementioned types: a deep learning approach where log-scaled mel-spectrograms are input to a convolutional neural network, and…
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21 Dec 2017 2 repositories listedFinally, a comprehensive review is presented on the proposed data set to fully advance the task of remote sensing caption.
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4 Oct 2016 2 repositories listedConvolutional Neural Networks (CNNs) have made remarkable progress on scene recognition, partially due to these recent large-scale scene datasets, such as the Places and Places2.
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20 May 2025 1 repository listedModern video understanding systems excel at tasks such as scene classification, object detection, and short video retrieval.
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3 May 2025 1 repository listedThis paper presents the Low-Complexity Acoustic Scene Classification with Device Information Task of the DCASE 2025 Challenge and its baseline system.
Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections