Semantic Segmentation

Benchmarks archive 2025-07-28

151 leaderboard tables shown for this task (1 more in the archive withheld as spam; see /not-shown), 150 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. 10 shown of 151 until expanded.

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

347 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 347 until expanded.

Subtasks archive 2025-07-28

29 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 6,644 papers with code (14,763 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.

• U-Net: Convolutional Networks for Biomedical Image Segmentation
  18 May 2015 487 repositories listed Syntology ran 510 of 757 samples · 247 unverified · 426 pointer-only (licence)
  There is large consent that successful training of deep networks requires many thousand annotated training samples.
• Deep Residual Learning for Image Recognition
  10 Dec 2015 484 repositories listed Syntology ran 230 of 377 samples · 147 unverified · 187 pointer-only (licence)
  Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.
• Mask R-CNN
  20 Mar 2017 179 repositories listed Syntology ran 42 of 140 samples · 98 unverified · 23 pointer-only (licence)
  Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
• MobileNetV2: Inverted Residuals and Linear Bottlenecks
  13 Jan 2018 159 repositories listed Syntology ran 85 of 111 samples · 26 unverified · 64 pointer-only (licence)
  In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes.
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
  22 Oct 2020 158 repositories listed Syntology ran 281 of 419 samples · 138 unverified · 154 pointer-only (licence)
  While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited.
• MMDetection: Open MMLab Detection Toolbox and Benchmark
  17 Jun 2019 142 repositories listed Syntology ran 14 of 82 samples · 68 unverified
  In this paper, we introduce the various features of this toolbox.
• PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
  2 Dec 2016 110 repositories listed Syntology ran 89 of 164 samples · 75 unverified · 90 pointer-only (licence)
  Point cloud is an important type of geometric data structure.
• FCOS: Fully Convolutional One-Stage Object Detection
  2 Apr 2019 87 repositories listed Syntology ran 13 of 40 samples · 27 unverified · 18 pointer-only (licence)
  By eliminating the predefined set of anchor boxes, FCOS completely avoids the complicated computation related to anchor boxes such as calculating overlapping during training.
• Feature Pyramid Networks for Object Detection
  9 Dec 2016 85 repositories listed Syntology ran 16 of 51 samples · 35 unverified · 11 pointer-only (licence)
  Feature pyramids are a basic component in recognition systems for detecting objects at different scales.
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
  25 Mar 2021 80 repositories listed Syntology ran 108 of 207 samples · 99 unverified · 43 pointer-only (licence)
  This paper presents a new vision Transformer, called Swin Transformer, that capably serves as a general-purpose backbone for computer vision.
• Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
  7 Feb 2018 78 repositories listed Syntology ran 43 of 72 samples · 29 unverified · 40 pointer-only (licence)
  The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter…
• Rethinking Atrous Convolution for Semantic Image Segmentation
  17 Jun 2017 77 repositories listed Syntology ran 3 of 7 samples · 4 unverified · 3 pointer-only (licence)
  To handle the problem of segmenting objects at multiple scales, we design modules which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates.
• SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
  2 Nov 2015 74 repositories listed Syntology ran 9 of 44 samples · 35 unverified · 10 pointer-only (licence)
  We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.
• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
  7 Jun 2017 68 repositories listed Syntology ran 36 of 67 samples · 31 unverified · 26 pointer-only (licence)
  By exploiting metric space distances, our network is able to learn local features with increasing contextual scales.
• Searching for MobileNetV3
  6 May 2019 67 repositories listed Syntology ran 58 of 105 samples · 47 unverified · 46 pointer-only (licence)
  We achieve new state of the art results for mobile classification, detection and segmentation.
• Pyramid Scene Parsing Network
  4 Dec 2016 67 repositories listed Syntology ran 7 of 29 samples · 22 unverified · 5 pointer-only (licence)
  Scene parsing is challenging for unrestricted open vocabulary and diverse scenes.
• Masked Autoencoders Are Scalable Vision Learners
  11 Nov 2021 58 repositories listed Syntology ran 71 of 137 samples · 66 unverified · 73 pointer-only (licence)
  Our MAE approach is simple: we mask random patches of the input image and reconstruct the missing pixels.
• A ConvNet for the 2020s
  10 Jan 2022 54 repositories listed Syntology ran 54 of 80 samples · 26 unverified · 11 pointer-only (licence)
  The "Roaring 20s" of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
• Fully Convolutional Networks for Semantic Segmentation
  14 Nov 2014 51 repositories listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  Convolutional networks are powerful visual models that yield hierarchies of features.
• ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
  7 Jun 2016 49 repositories listed Syntology ran 5 of 30 samples · 25 unverified
  The ability to perform pixel-wise semantic segmentation in real-time is of paramount importance in mobile applications.
• YOLACT: Real-time Instance Segmentation
  4 Apr 2019 48 repositories listed Syntology ran 10 of 21 samples · 11 unverified · 6 pointer-only (licence)
  Then we produce instance masks by linearly combining the prototypes with the mask coefficients.
• DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
  2 Jun 2016 47 repositories listed Syntology ran 28 of 63 samples · 35 unverified · 16 pointer-only (licence)
  ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales.
• Deep High-Resolution Representation Learning for Visual Recognition
  20 Aug 2019 42 repositories listed Syntology ran 3 of 34 samples · 31 unverified · 16 pointer-only (licence)
  High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection.
• High-Resolution Representations for Labeling Pixels and Regions
  9 Apr 2019 39 repositories listed Syntology ran 3 of 18 samples · 15 unverified · 5 pointer-only (licence)
  The proposed approach achieves superior results to existing single-model networks on COCO object detection.
• Deformable Convolutional Networks
  17 Mar 2017 38 repositories listed Syntology ran 3 of 9 samples · 6 unverified · 3 pointer-only (licence)
  Convolutional neural networks (CNNs) are inherently limited to model geometric transformations due to the fixed geometric structures in its building modules.
• Microsoft COCO: Common Objects in Context
  1 May 2014 38 repositories listed Syntology ran 1 of 7 samples · 6 unverified
  We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding.
• Attention U-Net: Learning Where to Look for the Pancreas
  11 Apr 2018 37 repositories listed Syntology ran 8 of 28 samples · 20 unverified · 7 pointer-only (licence)
  We propose a novel attention gate (AG) model for medical imaging that automatically learns to focus on target structures of varying shapes and sizes.
• Fully Convolutional Networks for Semantic Segmentation
  20 May 2016 37 repositories listed
  Convolutional networks are powerful visual models that yield hierarchies of features.
• ResNeSt: Split-Attention Networks
  19 Apr 2020 36 repositories listed Syntology ran 8 of 48 samples · 40 unverified · 23 pointer-only (licence)
  It is well known that featuremap attention and multi-path representation are important for visual recognition.
• YOLACT++: Better Real-time Instance Segmentation
  3 Dec 2019 36 repositories listed Syntology ran 11 of 43 samples · 32 unverified
  Then we produce instance masks by linearly combining the prototypes with the mask coefficients.

Syntology lines on 29 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.