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 1401–1450 of 2262 papers

TitleStatusHype
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification—0
Comparative analysis of deep learning approaches for AgNOR-stained cytology samples interpretation—0
Comparing YOLOv11 and YOLOv8 for instance segmentation of occluded and non-occluded immature green fruits in complex orchard environment—0
Comparing YOLOv8 and Mask RCNN for object segmentation in complex orchard environments—0
Comparison of UNet, ENet, and BoxENet for Segmentation of Mast Cells in Scans of Histological Slices—0
Competitive Learning for Achieving Content-specific Filters in Video Coding for Machines—0
CompetitorFormer: Competitor Transformer for 3D Instance Segmentation—0
Computation Reallocation for Object Detection—0
Computer Vision Pipeline for Automated Antarctic Krill Analysis—0
Concatenated Feature Pyramid Network for Instance Segmentation—0
Concavity-Induced Distance for Unoriented Point Cloud Decomposition—0
ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models—0
Confidence Calibration for Object Detection and Segmentation—0
ConfLUNet: Multiple sclerosis lesion instance segmentation in presence of confluent lesions—0
Instance Scale Normalization for image understanding—0
Consistent Video Instance Segmentation with Inter-Frame Recurrent Attention—0
Content-Aware Multi-Level Guidance for Interactive Instance Segmentation—0
Context-Preserving Instance-Level Augmentation and Deformable Convolution Networks for SAR Ship Detection—0
Contextual Graph Reasoning Networks—0
Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation—0
Continental-Scale Building Detection from High Resolution Satellite Imagery—0
Contour Loss for Instance Segmentation via k-step Distance Transformation Image—0
ContourRender: Detecting Arbitrary Contour Shape For Instance Segmentation In One Pass—0
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation—0
Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray—0
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning—0
CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks—0
AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss—0
Could Giant Pretrained Image Models Extract Universal Representations?—0
Counting and Segmenting Sorghum Heads—0
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks—0
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds—0
Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation—0
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics—0
CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation—0
Curriculum Learning with Diversity for Supervised Computer Vision Tasks—0
Task-Specific Adaptation of Segmentation Foundation Model via Prompt Learning—0
CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation—0
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx—0
DArch: Dental Arch Prior-assisted 3D Tooth Instance Segmentation—0
DArch: Dental Arch Prior-Assisted 3D Tooth Instance Segmentation With Weak Annotations—0
DARNet: Deep Active Ray Network for Building Segmentation—0
Darwin's Neural Network: AI-based Strategies for Rapid and Scalable Cell and Coronavirus Screening—0
Cross-Task Data Augmentation by Pseudo-label Generation for Region Based Coronary Artery Instance Segmentation—0
Data-Centric Learning Framework for Real-Time Detection of Aiming Beam in Fluorescence Lifetime Imaging Guided Surgery—0
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision—0
3rd Place Scheme on Instance Segmentation Track of ICCV 2021 VIPriors Challenges—0
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model—0
Decoupled Motion Expression Video Segmentation—0
Dedicated Inference Engine and Binary-Weight Neural Networks for Lightweight Instance Segmentation—0
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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