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 301325 of 2262 papers

TitleStatusHype
Compositional Human-Scene Interaction Synthesis with Semantic ControlCode1
Container: Context Aggregation NetworksCode1
Conditional Object-Centric Learning from VideoCode1
Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive FusionCode1
Commonality-Parsing Network across Shape and Appearance for Partially Supervised Instance SegmentationCode1
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachCode1
FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance SegmentationCode1
Boundary-assisted Region Proposal Networks for Nucleus SegmentationCode1
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance SegmentationCode1
An Instance Segmentation Dataset of Yeast Cells in MicrostructuresCode1
Efficient Attention: Attention with Linear ComplexitiesCode1
BoundarySqueeze: Image Segmentation as Boundary SqueezingCode1
Common Limitations of Image Processing Metrics: A Picture StoryCode1
FAPIS: A Few-shot Anchor-free Part-based Instance SegmenterCode1
Fashionpedia: Ontology, Segmentation, and an Attribute Localization DatasetCode1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
BoxeR: Box-Attention for 2D and 3D TransformersCode1
Continuous Copy-Paste for One-Stage Multi-Object Tracking and SegmentationCode1
BlendMask: Top-Down Meets Bottom-Up for Instance SegmentationCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
BoxSnake: Polygonal Instance Segmentation with Box SupervisionCode1
CompFeat: Comprehensive Feature Aggregation for Video Instance SegmentationCode1
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance SegmentationCode1
BoxVIS: Video Instance Segmentation with Box AnnotationsCode1
MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and ResolutionCode1
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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