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 451475 of 2262 papers

TitleStatusHype
Deep Variational Instance SegmentationCode1
Affinity Attention Graph Neural Network for Weakly Supervised Semantic SegmentationCode1
Augmentation for small object detectionCode1
Contextual Transformer Networks for Visual RecognitionCode1
GradAug: A New Regularization Method for Deep Neural NetworksCode1
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
AugmenTory: A Fast and Flexible Polygon Augmentation LibraryCode1
Contour Proposal Networks for Biomedical Instance SegmentationCode1
A Close Look at Spatial Modeling: From Attention to ConvolutionCode1
Interactive Object Segmentation in 3D Point CloudsCode1
Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point CloudsCode1
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance SegmentationCode1
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
MPViT: Multi-Path Vision Transformer for Dense PredictionCode1
Hard Negative Mixing for Contrastive LearningCode1
Detect, consolidate, delineate: scalable mapping of field boundaries using satellite imagesCode1
Co-Scale Conv-Attentional Image TransformersCode1
AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D ScansCode1
Hierarchical Aggregation for 3D Instance SegmentationCode1
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayersCode1
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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