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 10011025 of 2262 papers

TitleStatusHype
Cell tracking for live-cell microscopy using an activity-prioritized assignment strategyCode0
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic SegmentationCode0
Panoptic-DeepLabCode0
TensorMask: A Foundation for Dense Object SegmentationCode0
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually ImpairedCode0
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAMCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
CCNet: Criss-Cross Attention for Semantic SegmentationCode0
Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped AttentionCode0
Eosinophils Instance Object Segmentation on Whole Slide Imaging Using Multi-label Circle RepresentationCode0
CBNet: A Novel Composite Backbone Network Architecture for Object DetectionCode0
Palmira: A Deep Deformable Network for Instance Segmentation of Dense and Uneven Layouts in Handwritten ManuscriptsCode0
EOLO: Embedded Object Segmentation only Look OnceCode0
ENSeg: A Novel Dataset and Method for the Segmentation of Enteric Neuron Cells on Microscopy ImagesCode0
Enhancing Generic Segmentation with Learned Region RepresentationsCode0
One Step Learning, One Step ReviewCode0
Enhanced Masked Image Modeling for Analysis of Dental Panoramic RadiographsCode0
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy ImagesCode0
Cascade R-CNN: High Quality Object Detection and Instance SegmentationCode0
End-to-end video instance segmentation via spatial-temporal graph neural networksCode0
One-stage Video Instance Segmentation: From Frame-in Frame-out to Clip-in Clip-outCode0
CARAFE: Content-Aware ReAssembly of FEaturesCode0
AdaContour: Adaptive Contour Descriptor with Hierarchical RepresentationCode0
End-to-End Learned Random Walker for Seeded Image SegmentationCode0
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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