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

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Showing 201–250 of 2262 papers

TitleStatusHype
Comparing YOLOv11 and YOLOv8 for instance segmentation of occluded and non-occluded immature green fruits in complex orchard environment—0
Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks—0
YOLOv11: An Overview of the Key Architectural EnhancementsCode0
EPContrast: Effective Point-level Contrastive Learning for Large-scale Point Cloud Understanding—0
NucleiMix: Realistic Data Augmentation for Nuclei Instance Segmentation—0
DI-MaskDINO: A Joint Object Detection and Instance Segmentation ModelCode2
PlaneSAM: Multimodal Plane Instance Segmentation Using the Segment Anything Model—0
Integrated Image-Text Based on Semi-supervised Learning for Small Sample Instance Segmentation—0
Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume MixingCode0
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy ImagesCode0
Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology—0
LESS: Label-Efficient and Single-Stage Referring 3D SegmentationCode1
SDI-Paste: Synthetic Dynamic Instance Copy-Paste for Video Instance Segmentation—0
Fractal Calibration for long-tailed object detectionCode0
V2M: Visual 2-Dimensional Mamba for Image Representation LearningCode1
Segmenting objects with Bayesian fusion of active contour models and convnet priors—0
QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space ModelCode1
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts—0
Real-time Ship Recognition and Georeferencing for the Improvement of Maritime Situational Awareness—0
ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method—0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
Polyp-SES: Automatic Polyp Segmentation with Self-Enriched Semantic ModelCode0
Optimizing Drug Delivery in Smart Pharmacies: A Novel Framework of Multi-Stage Grasping Network Combined with Adaptive Robotics Mechanism—0
Search3D: Hierarchical Open-Vocabulary 3D Segmentation—0
ProMerge: Prompt and Merge for Unsupervised Instance Segmentation—0
Efficient Microscopic Image Instance Segmentation for Food Crystal Quality Control—0
Amodal Instance Segmentation with Diffusion Shape Prior Estimation—0
Instance Segmentation of Reinforced Concrete Bridges with Synthetic Point Clouds—0
Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary SegmentationCode2
Adapting Segment Anything Model for Unseen Object Instance Segmentation—0
SOS: Segment Object System for Open-World Instance Segmentation With Object PriorsCode0
Lidar Panoptic Segmentation in an Open WorldCode1
Foundation Models for Amodal Video Instance Segmentation in Automated DrivingCode0
GAInS: Gradient Anomaly-aware Biomedical Instance SegmentationCode1
Applications of Knowledge Distillation in Remote Sensing: A Survey—0
Are Deep Learning Models Robust to Partial Object Occlusion in Visual Recognition Tasks?—0
Resolving Inconsistent Semantics in Multi-Dataset Image Segmentation—0
LACOSTE: Exploiting stereo and temporal contexts for surgical instrument segmentation—0
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory AnnotationsCode0
One missing piece in Vision and Language: A Survey on Comics UnderstandingCode2
Bayesian Self-Training for Semi-Supervised 3D Segmentation—0
UNIT: Unsupervised Online Instance Segmentation through Time—0
Insight Any Instance: Promptable Instance Segmentation for Remote Sensing Images—0
Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodes—0
CISCA and CytoDArk0: a Cell Instance Segmentation and Classification method for histo(patho)logical image Analyses and a new, open, Nissl-stained dataset for brain cytoarchitecture studiesCode1
Automatic occlusion removal from 3D maps for maritime situational awareness—0
MouseSIS: A Frames-and-Events Dataset for Space-Time Instance Segmentation of MiceCode1
iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation—0
Evaluation Study on SAM 2 for Class-agnostic Instance-level SegmentationCode1
MetaFood3D: 3D Food Dataset with Nutrition Values—0
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All datasetsCOCO test-devCOCO minivalLVIS v1.0 valCityscapes valADE20K valARMBenchOccluded COCOOoDISSeparated COCOTBBRBDD100K valCOCO val (panoptic labels)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8—Unverified
2ResNeSt-200 (multi-scale)AP5070.2—Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2—Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8—Unverified
5Co-DETRmask AP57.1—Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1—Unverified
7ISDA (ResNet-50)APL55.7—Unverified
8EVAmask AP55.5—Unverified
9FD-SwinV2-Gmask AP55.4—Unverified
10Mask Frozen-DETRmask AP55.3—Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501—Unverified
2Co-DETRmask AP56.6—Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9—Unverified
4InternImage-Hmask AP55.4—Unverified
5EVAmask AP55—Unverified
6Mask Frozen-DETRmask AP54.9—Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5—Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2—Unverified
9GLEE-Promask AP54.2—Unverified
10SwinV2-G (HTC++)mask AP53.7—Unverified