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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1226–1250 of 2262 papers

TitleStatusHype
Adapting Segment Anything Model for Unseen Object Instance Segmentation—0
Adapting Vision Foundation Models for Plant Phenotyping—0
Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation—0
A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing—0
A Dataset for Lane Instance Segmentation in Urban Environments—0
ADFQ-ViT: Activation-Distribution-Friendly Post-Training Quantization for Vision Transformers—0
Advances in Kidney Biopsy Lesion Assessment through Dense Instance Segmentation—0
Advancing Manga Analysis: Comprehensive Segmentation Annotations for the Manga109 Dataset—0
Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism—0
Advancing SEM Based Nano-Scale Defect Analysis in Semiconductor Manufacturing for Advanced IC Nodes—0
Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation—0
A Dynamic Feature Interaction Framework for Multi-task Visual Perception—0
A Fully Unsupervised Instance Segmentation Technique for White Blood Cell Images—0
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation—0
Aggregation With Feature Detection—0
A Graph Matching Perspective With Transformers on Video Instance Segmentation—0
AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model—0
A Histogram Thresholding Improvement to Mask R-CNN for Scalable Segmentation of New and Old Rural Buildings—0
A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection—0
AI-based thermal bridge detection of building rooftops on district scale using aerial images—0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers—0
ALBERT: Advanced Localization and Bidirectional Encoder Representations from Transformers for Automotive Damage Evaluation—0
Aligning Instance-Semantic Sparse Representation towards Unsupervised Object Segmentation and Shape Abstraction with Repeatable Primitives—0
All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes—0
All You Need is a Second Look: Towards Arbitrary-Shaped Text Detection—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