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 9761000 of 2262 papers

TitleStatusHype
NucleiMix: Realistic Data Augmentation for Nuclei Instance Segmentation0
EPContrast: Effective Point-level Contrastive Learning for Large-scale Point Cloud Understanding0
PlaneSAM: Multimodal Plane Instance Segmentation Using the Segment Anything Model0
Integrated Image-Text Based on Semi-supervised Learning for Small Sample Instance Segmentation0
Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume MixingCode0
Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology0
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy ImagesCode0
SDI-Paste: Synthetic Dynamic Instance Copy-Paste for Video Instance Segmentation0
Fractal Calibration for long-tailed object detectionCode0
Segmenting objects with Bayesian fusion of active contour models and convnet priors0
Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts0
Real-time Ship Recognition and Georeferencing for the Improvement of Maritime Situational Awareness0
ProtoSeg: A Prototype-Based Point Cloud Instance Segmentation Method0
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 Mechanism0
Search3D: Hierarchical Open-Vocabulary 3D Segmentation0
ProMerge: Prompt and Merge for Unsupervised Instance Segmentation0
Efficient Microscopic Image Instance Segmentation for Food Crystal Quality Control0
Amodal Instance Segmentation with Diffusion Shape Prior Estimation0
Instance Segmentation of Reinforced Concrete Bridges with Synthetic Point Clouds0
Adapting Segment Anything Model for Unseen Object Instance Segmentation0
SOS: Segment Object System for Open-World Instance Segmentation With Object Priors0
Foundation Models for Amodal Video Instance Segmentation in Automated DrivingCode0
Applications of Knowledge Distillation in Remote Sensing: A Survey0
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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