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 601625 of 2262 papers

TitleStatusHype
CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation0
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification0
Zero-Shot Refinement of Buildings' Segmentation Models using SAMCode1
LoCUS: Learning Multiscale 3D-consistent Features from Posed Images0
Adapting Vision Foundation Models for Plant Phenotyping0
Self-supervised Learning of Contextualized Local Visual EmbeddingsCode0
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore ModelingCode1
Advances in Kidney Biopsy Lesion Assessment through Dense Instance Segmentation0
YOLOR-Based Multi-Task LearningCode5
CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding0
Mask4Former: Mask Transformer for 4D Panoptic SegmentationCode1
Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Clouds0
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling0
MoCaE: Mixture of Calibrated Experts Significantly Improves Object DetectionCode1
3D Indoor Instance Segmentation in an Open-WorldCode1
Automatic Animation of Hair Blowing in Still Portrait Photos0
A SAM-based Solution for Hierarchical Panoptic Segmentation of Crops and Weeds Competition0
GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation0
ClusterFormer: Clustering As A Universal Visual LearnerCode1
MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance SegmentationCode1
NeuralLabeling: A versatile toolset for labeling vision datasets using Neural Radiance FieldsCode1
TCOVIS: Temporally Consistent Online Video Instance SegmentationCode0
RMT: Retentive Networks Meet Vision TransformersCode2
Intelligent Debris Mass Estimation Model for Autonomous Underwater Vehicle0
Uncertainty Estimation in Instance Segmentation with Star-convex Shapes0
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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