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 351375 of 2262 papers

TitleStatusHype
DropLoss for Long-Tail Instance SegmentationCode1
An Instance Segmentation Dataset of Yeast Cells in MicrostructuresCode1
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance SegmentationCode1
Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing ImagesCode1
Distilling Knowledge via Knowledge ReviewCode1
Boundary-assisted Region Proposal Networks for Nucleus SegmentationCode1
A Comparative Evaluation of Deep Learning Techniques for Photovoltaic Panel Detection from Aerial ImagesCode1
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and trackingCode1
Distribution Alignment: A Unified Framework for Long-tail Visual RecognitionCode1
Deep High-Resolution Representation Learning for Visual RecognitionCode1
Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological ImagesCode1
DilateFormer: Multi-Scale Dilated Transformer for Visual RecognitionCode1
DIOD: Self-Distillation Meets Object DiscoveryCode1
FinnWoodlands DatasetCode1
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box SupervisionCode1
DVIS: Decoupled Video Instance Segmentation FrameworkCode1
Detection and Segmentation of Lesion Areas in Chest CT Scans For The Prediction of COVID-19Code1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
FourierNet: Compact mask representation for instance segmentation using differentiable shape decodersCode1
CenterMask : Real-Time Anchor-Free Instance SegmentationCode1
CenterMask: Real-Time Anchor-Free Instance SegmentationCode1
FsaNet: Frequency Self-attention for Semantic SegmentationCode1
Detect, consolidate, delineate: scalable mapping of field boundaries using satellite imagesCode1
CentripetalNet: Pursuing High-quality Keypoint Pairs for Object DetectionCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
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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