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 14261450 of 2262 papers

TitleStatusHype
Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors0
MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation0
Mask Encoding for Single Shot Instance Segmentation0
Mask-free OVIS: Open-Vocabulary Instance Segmentation without Manual Mask Annotations0
Mask Frozen-DETR: High Quality Instance Segmentation with One GPU0
MaskGroup: Hierarchical Point Grouping and Masking for 3D Instance Segmentation0
Mask-Guided Matting in the Wild0
Mask-guided sample selection for Semi-Supervised Instance Segmentation0
Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection0
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features0
MaskPlus: Improving Mask Generation for Instance Segmentation0
Joint Object Contour Points and Semantics for Instance Segmentation0
Mask Propagation Network for Video Object Segmentation0
MaskUno: Switch-Split Block For Enhancing Instance Segmentation0
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors0
Maximal Cliques on Multi-Frame Proposal Graph for Unsupervised Video Object Segmentation0
McGAN: Generating Manufacturable Designs by Embedding Manufacturing Rules into Conditional Generative Adversarial Network0
Memory Efficient Transformer Adapter for Dense Predictions0
MeNToS: Tracklets Association with a Space-Time Memory Network0
MetaFood3D: 3D Food Dataset with Nutrition Values0
Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art0
MGTUNet: An new UNet for colon nuclei instance segmentation and quantification0
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images0
Minimizing Labeled, Maximizing Unlabeled: An Image-Driven Approach for Video Instance Segmentation0
Mirror-Yolo: A Novel Attention Focus, Instance Segmentation and Mirror Detection Model0
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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