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

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Showing 401–450 of 2262 papers

TitleStatusHype
Clustering Plotted Data by Image SegmentationCode1
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree NetworksCode1
A Deep Learning Approach to Teeth Segmentation and Orientation from Panoramic X-raysCode1
CLUSTSEG: Clustering for Universal SegmentationCode1
Eigencontours: Novel Contour Descriptors Based on Low-Rank ApproximationCode1
Instance-wise Depth and Motion Learning from Monocular VideosCode1
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance SegmentationCode1
End-to-End Referring Video Object Segmentation with Multimodal TransformersCode1
Explain Any Concept: Segment Anything Meets Concept-Based ExplanationCode1
Inter-Instance Similarity Modeling for Contrastive LearningCode1
Coherent Reconstruction of Multiple Humans from a Single ImageCode1
A Structure-Aware Relation Network for Thoracic Diseases Detection and SegmentationCode1
Efficient Multi-Task RGB-D Scene Analysis for Indoor EnvironmentsCode1
D2Det: Towards High Quality Object Detection and Instance SegmentationCode1
A Survey of Self-Supervised and Few-Shot Object DetectionCode1
Kartezio: Evolutionary Design of Explainable Pipelines for Biomedical Image AnalysisCode1
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachCode1
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale AmbiguitiesCode1
EfficientPS: Efficient Panoptic SegmentationCode1
Commonality-Parsing Network across Shape and Appearance for Partially Supervised Instance SegmentationCode1
Common Limitations of Image Processing Metrics: A Picture StoryCode1
Effective Self-supervised Pre-training on Low-compute Networks without DistillationCode1
LeafMask: Towards Greater Accuracy on Leaf SegmentationCode1
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub RobotCode1
Asymmetric Patch Sampling for Contrastive LearningCode1
Learning Cross-Representation Affinity Consistency for Sparsely Supervised Biomedical Instance SegmentationCode1
Learning Inter-Superpoint Affinity for Weakly Supervised 3D Instance SegmentationCode1
CompFeat: Comprehensive Feature Aggregation for Video Instance SegmentationCode1
Complete Instances Mining for Weakly Supervised Instance SegmentationCode1
EDAPS: Enhanced Domain-Adaptive Panoptic SegmentationCode1
Compositional Human-Scene Interaction Synthesis with Semantic ControlCode1
A Transductive Approach for Video Object SegmentationCode1
A Tri-Layer Plugin to Improve Occluded DetectionCode1
Learning Saliency Propagation for Semi-Supervised Instance SegmentationCode1
Learning with Noisy Class Labels for Instance SegmentationCode1
Conditional Convolutions for Instance SegmentationCode1
Less is More: Pay Less Attention in Vision TransformersCode1
Conditional Object-Centric Learning from VideoCode1
Efficient Connectivity-Preserving Instance Segmentation with Supervoxel-Based Loss FunctionCode1
LGD: Label-guided Self-distillation for Object DetectionCode1
Attention-Based Transformers for Instance Segmentation of Cells in MicrostructuresCode1
Conformer: Local Features Coupling Global Representations for Visual RecognitionCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
LineFormer: Rethinking Line Chart Data Extraction as Instance SegmentationCode1
Container: Context Aggregation NetworkCode1
Container: Context Aggregation NetworksCode1
BlendMask: Top-Down Meets Bottom-Up for Instance SegmentationCode1
MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and ResolutionCode1
ContourFormer:Real-Time Contour-Based End-to-End Instance Segmentation TransformerCode1
Efficient Self-supervised Vision Pretraining with Local Masked ReconstructionCode1
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All datasetsCOCO test-devCOCO minivalLVIS v1.0 valCityscapes valADE20K valARMBenchOccluded COCOOoDISSeparated COCOTBBRBDD100K valCOCO val (panoptic labels)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8—Unverified
2ResNeSt-200 (multi-scale)AP5070.2—Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2—Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8—Unverified
5Co-DETRmask AP57.1—Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1—Unverified
7ISDA (ResNet-50)APL55.7—Unverified
8EVAmask AP55.5—Unverified
9FD-SwinV2-Gmask AP55.4—Unverified
10Mask Frozen-DETRmask AP55.3—Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501—Unverified
2Co-DETRmask AP56.6—Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9—Unverified
4InternImage-Hmask AP55.4—Unverified
5EVAmask AP55—Unverified
6Mask Frozen-DETRmask AP54.9—Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5—Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2—Unverified
9GLEE-Promask AP54.2—Unverified
10SwinV2-G (HTC++)mask AP53.7—Unverified