SOTAVerified

Instance Segmentation

Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.

Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21

Papers

Showing 21512200 of 2262 papers

TitleStatusHype
AutoKary2022: A Large-Scale Densely Annotated Dataset for Chromosome Instance SegmentationCode0
Semantic Information in Contrastive LearningCode0
D-InLoc++: Indoor Localization in Dynamic EnvironmentsCode0
DetNet: A Backbone network for Object DetectionCode0
Semantic Instance Segmentation via Deep Metric LearningCode0
Semantic Instance Segmentation with a Discriminative Loss FunctionCode0
Mapping urban large-area advertising structures using drone imagery and deep learning-based spatial data analysisCode0
Detection of Tumour Infiltrating Lymphocytes in CD3 and CD8 Stained Histopathological Images using a Two-Phase Deep CNNCode0
M^6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout AnalysisCode0
Deformable VisTR: Spatio temporal deformable attention for video instance segmentationCode0
A Unified Query-based Paradigm for Camouflaged Instance SegmentationCode0
Attentive NormalizationCode0
Deep Watershed Transform for Instance SegmentationCode0
Affinity Derivation and Graph Merge for Instance SegmentationCode0
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy ImagesCode0
M18K: A Comprehensive RGB-D Dataset and Benchmark for Mushroom Detection and Instance SegmentationCode0
DeepSportLab: a Unified Framework for Ball Detection, Player Instance Segmentation and Pose Estimation in Team Sports ScenesCode0
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware AssociationCode0
Localizing Infinity-shaped fishes: Sketch-guided object localization in the wildCode0
Local Context Normalization: Revisiting Local NormalizationCode0
Relevance Attack on DetectorsCode0
Leveraging Vision-Language Models for Open-Vocabulary Instance Segmentation and TrackingCode0
Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted MulticutsCode0
Learning Video Object Segmentation from Static ImagesCode0
TWIST: Two-Way Inter-Label Self-Training for Semi-Supervised 3D Instance SegmentationCode0
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance SegmentationCode0
Deeply Shape-guided Cascade for Instance SegmentationCode0
Where are the Masks: Instance Segmentation with Image-level SupervisionCode0
ShapeFormer: Shape Prior Visible-to-Amodal Transformer-based Amodal Instance SegmentationCode0
Two-Level Temporal Relation Model for Online Video Instance SegmentationCode0
A Feasible Framework for Arbitrary-Shaped Scene Text RecognitionCode0
4D Generic Video Object ProposalsCode0
Zero-Shot Enhancement of Low-Light Image Based on Retinex DecompositionCode0
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s AlphaCode0
Deep Spectral Improvement for Unsupervised Image Instance SegmentationCode0
Learning to Segment via Cut-and-PasteCode0
Deep Level Set for Box-supervised Instance Segmentation in Aerial ImagesCode0
Learning to Segment Every ThingCode0
Associatively Segmenting Instances and Semantics in Point CloudsCode0
Signature and Log-signature for the Study of Empirical Distributions Generated with GANsCode0
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video DecompositionCode0
Learning to See the Invisible: End-to-End Trainable Amodal Instance SegmentationCode0
Associative Embedding: End-to-End Learning for Joint Detection and GroupingCode0
Learning to Cluster for Proposal-Free Instance SegmentationCode0
Deep Learning for Morphological Identification of Extended Radio Galaxies using Weak LabelsCode0
Learning Semantics-aware Distance Map with Semantics Layering Network for Amodal Instance SegmentationCode0
Uncertainty Calibration and its Application to Object DetectionCode0
Learning Rich Features from RGB-D Images for Object Detection and SegmentationCode0
Assessment of Cell Nuclei AI Foundation Models in Kidney PathologyCode0
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human ParsingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8Unverified
2ResNeSt-200 (multi-scale)AP5070.2Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8Unverified
5Co-DETRmask AP57.1Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1Unverified
7ISDA (ResNet-50)APL55.7Unverified
8EVAmask AP55.5Unverified
9FD-SwinV2-Gmask AP55.4Unverified
10Mask Frozen-DETRmask AP55.3Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501Unverified
2Co-DETRmask AP56.6Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9Unverified
4InternImage-Hmask AP55.4Unverified
5EVAmask AP55Unverified
6Mask Frozen-DETRmask AP54.9Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2Unverified
9GLEE-Promask AP54.2Unverified
10SwinV2-G (HTC++)mask AP53.7Unverified