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 451–500 of 2262 papers

TitleStatusHype
Audio-Visual Instance SegmentationCode1
Affinity Attention Graph Neural Network for Weakly Supervised Semantic SegmentationCode1
Augmentation for small object detectionCode1
Contextual Transformer Networks for Visual RecognitionCode1
MDQE: Mining Discriminative Query Embeddings to Segment Occluded Instances on Challenging VideosCode1
Continual Learning for Image Segmentation with Dynamic QueryCode1
Continuous Copy-Paste for One-Stage Multi-Object Tracking and SegmentationCode1
ContourFormer:Real-Time Contour-Based End-to-End Instance Segmentation TransformerCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
Contour Proposal Networks for Biomedical Instance SegmentationCode1
Microsoft COCO: Common Objects in ContextCode1
MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAMCode1
BlendMask: Top-Down Meets Bottom-Up for Instance SegmentationCode1
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive FusionCode1
Contrastive Object-level Pre-training with Spatial Noise Curriculum LearningCode1
ContrastMask: Contrastive Learning to Segment Every ThingCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
AggMask: Exploring locally aggregated learning of mask representations for instance segmentationCode1
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision ModelsCode1
MobileViG: Graph-Based Sparse Attention for Mobile Vision ApplicationsCode1
EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention FusionCode1
Co-Scale Conv-Attentional Image TransformersCode1
AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D ScansCode1
MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance SegmentationCode1
MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and ResolutionCode1
MSNet: A Multilevel Instance Segmentation Network for Natural Disaster Damage Assessment in Aerial VideosCode1
Multiclass Weighted Loss for Instance Segmentation of Cluttered CellsCode1
COVID-CT-Mask-Net: Prediction of COVID-19 from CT Scans Using Regional FeaturesCode1
EPSANet: An Efficient Pyramid Squeeze Attention Block on Convolutional Neural NetworkCode1
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object DetectionCode1
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image EncodingCode1
CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode1
End-to-End Referring Video Object Segmentation with Multimodal TransformersCode1
End-to-End Human Instance MattingCode1
Crossover Learning for Fast Online Video Instance SegmentationCode1
Cross-View Regularization for Domain Adaptive Panoptic SegmentationCode1
End-to-End Semi-Supervised Object Detection with Soft TeacherCode1
CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological ImagesCode1
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological ImagesCode1
CTVIS: Consistent Training for Online Video Instance SegmentationCode1
A Close Look at Spatial Modeling: From Attention to ConvolutionCode1
Occluded Video Instance Segmentation: A BenchmarkCode1
EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance SegmentationCode1
End-to-End Video Instance Segmentation with TransformersCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point CloudsCode1
CycleMLP: A MLP-like Architecture for Dense PredictionCode1
ElC-OIS: Ellipsoidal Clustering for Open-World Instance Segmentation on LiDAR DataCode1
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance SegmentationCode1
ELSA: Enhanced Local Self-Attention for Vision TransformerCode1
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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