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 551600 of 2262 papers

TitleStatusHype
Efficient Multi-Task RGB-D Scene Analysis for Indoor EnvironmentsCode1
3D Indoor Instance Segmentation in an Open-WorldCode1
Evaluation of Segment Anything Model 2: The Role of SAM2 in the Underwater EnvironmentCode1
Improving Weakly-supervised Video Instance Segmentation by Leveraging Spatio-temporal ConsistencyCode1
Eigencontours: Novel Contour Descriptors Based on Low-Rank ApproximationCode1
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality AnnotationsCode1
Deep Structured Instance Graph for Distilling Object DetectorsCode1
ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR DataCode1
Deep Variational Instance SegmentationCode1
3D Instances as 1D KernelsCode1
Betrayed by Captions: Joint Caption Grounding and Generation for Open Vocabulary Instance SegmentationCode1
EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance SegmentationCode1
Deformable ConvNets v2: More Deformable, Better ResultsCode1
Amodal Intra-class Instance Segmentation: Synthetic Datasets and BenchmarkCode1
MMDetection: Open MMLab Detection Toolbox and BenchmarkCode1
EfficientPS: Efficient Panoptic SegmentationCode1
Delving Deeper into Anti-aliasing in ConvNetsCode1
DenseCLIP: Language-Guided Dense Prediction with Context-Aware PromptingCode1
Dense Contrastive Learning for Self-Supervised Visual Pre-TrainingCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
Metrics reloaded: Recommendations for image analysis validationCode1
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance SegmentationCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
Depth-aware Object Segmentation and Grasp Detection for Robotic Picking TasksCode1
MitoEM Dataset: Large-scale 3D Mitochondria Instance Segmentation from EM ImagesCode1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object DetectionCode1
Evaluation Study on SAM 2 for Class-agnostic Instance-level SegmentationCode1
MSeg: A Composite Dataset for Multi-domain Semantic SegmentationCode1
Deep-learning in the bioimaging wild: Handling ambiguous data with deepflash2Code1
Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point CloudsCode1
Detect, consolidate, delineate: scalable mapping of field boundaries using satellite imagesCode1
A Close Look at Spatial Modeling: From Attention to ConvolutionCode1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene ContextsCode1
Detection and Segmentation of Lesion Areas in Chest CT Scans For The Prediction of COVID-19Code1
Exploring Classification Equilibrium in Long-Tailed Object DetectionCode1
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance SegmentationCode1
Mask Transfiner for High-Quality Instance SegmentationCode1
DynaMask: Dynamic Mask Selection for Instance SegmentationCode1
Deep Learning based Food Instance Segmentation using Synthetic DataCode1
MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and ResolutionCode1
Dynamic Convolution for 3D Point Cloud Instance SegmentationCode1
DVIS++: Improved Decoupled Framework for Universal Video SegmentationCode1
DeVIS: Making Deformable Transformers Work for Video Instance SegmentationCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
DVIS: Decoupled Video Instance Segmentation FrameworkCode1
DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic ConvolutionCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
EDAPS: Enhanced Domain-Adaptive Panoptic SegmentationCode1
MassMIND: Massachusetts Maritime INfrared DatasetCode1
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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