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 9511000 of 2262 papers

TitleStatusHype
FrGNet: A fourier-guided weakly-supervised framework for nuclear instance segmentationCode0
A 3D Convolutional Approach to Spectral Object Segmentation in Space and TimeCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
Precise Location Matching Improves Dense Contrastive Learning in Digital PathologyCode0
Predicting Future Instance Segmentation by Forecasting Convolutional FeaturesCode0
Single Network Panoptic Segmentation for Street Scene UnderstandingCode0
A Spacecraft Dataset for Detection, Segmentation and Parts RecognitionCode0
PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and ClassificationCode0
Fractal Calibration for long-tailed object detectionCode0
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s AlphaCode0
PPR-Net:Point-wise Pose Regression Network for Instance Segmentation and 6D Pose Estimation in Bin-picking ScenariosCode0
CLIMB-3D: Continual Learning for Imbalanced 3D Instance SegmentationCode0
Foveated Instance SegmentationCode0
PolyTransform: Deep Polygon Transformer for Instance SegmentationCode0
Pose2Seg: Detection Free Human Instance SegmentationCode0
Foundation Models for Amodal Video Instance Segmentation in Automated DrivingCode0
A Simple Single-Scale Vision Transformer for Object Localization and Instance SegmentationCode0
Polyp-SES: Automatic Polyp Segmentation with Self-Enriched Semantic ModelCode0
PM-VIS+: High-Performance Video Instance Segmentation without Video AnnotationCode0
Fine-grained Background Representation for Weakly Supervised Semantic SegmentationCode0
Point Cloud Instance Segmentation with Semi-supervised Bounding-Box MiningCode0
CircleSnake: Instance Segmentation with Circle RepresentationCode0
Circle Representation for Medical Instance Object SegmentationCode0
SCD: A Stacked Carton Dataset for Detection and SegmentationCode0
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding ModelCode0
Medical Image Fusion for High-Level Analysis: A Mutual Enhancement Framework for Unaligned PAT and MRICode0
AdaptIS: Adaptive Instance Selection NetworkCode0
Fast Segment AnythingCode0
Fast Scene Understanding for Autonomous DrivingCode0
Faster Training of Mask R-CNN by Focusing on Instance BoundariesCode0
PatchDCT: Patch Refinement for High Quality Instance SegmentationCode0
Fashion-Guided Adversarial Attack on Person SegmentationCode0
False Negative Reduction in Video Instance Segmentation using Uncertainty EstimatesCode0
PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAMCode0
Partial-Attribution Instance Segmentation for Astronomical Source Detection and DeblendingCode0
Exploring Target Representations for Masked AutoencodersCode0
Artificial Intelligence-driven Image Analysis of Bacterial Cells and BiofilmsCode0
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually ImpairedCode0
CenterDisks: Real-time instance segmentation with disk coveringCode0
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object UnderstandingCode0
Exploiting Depth Information for Wildlife MonitoringCode0
Explicit Shape Encoding for Real-Time Instance SegmentationCode0
CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell Segmentation and Tracking in Microscopy ImagesCode0
Cell tracking for live-cell microscopy using an activity-prioritized assignment strategyCode0
Panoptic-DeepLabCode0
Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped AttentionCode0
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
Palmira: A Deep Deformable Network for Instance Segmentation of Dense and Uneven Layouts in Handwritten ManuscriptsCode0
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic SegmentationCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
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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