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 1551–1600 of 2262 papers

TitleStatusHype
Fast and Precise Binary Instance Segmentation of 2D Objects for Automotive Applications—0
FLIC: Fast Lidar Image Clustering—0
Fast Single-shot Ship Instance Segmentation Based on Polar Template Mask in Remote Sensing Images—0
Multi-Scale Denoising in the Feature Space for Low-Light Instance Segmentation—0
Feature Pyramid Transformer—0
Few-shot adaptation for morphology-independent cell instance segmentation—0
Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentation—0
FGN: Fully Guided Network for Few-Shot Instance Segmentation—0
Fine-grained building roof instance segmentation based on domain adapted pretraining and composite dual-backbone—0
FISBe: A Real-World Benchmark Dataset for Instance Segmentation of Long-Range Thin Filamentous Structures—0
FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving—0
FlowCut: Unsupervised Video Instance Segmentation via Temporal Mask Matching—0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping—0
Foreign object segmentation in chest x-rays through anatomy-guided shape insertion—0
FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees—0
FourierMask: Instance Segmentation using Fourier Mapping in Implicit Neural Networks—0
FoxInst: A Frustratingly Simple Baseline for Weakly Few-shot Instance Segmentation—0
FPCD: An Open Aerial VHR Dataset for Farm Pond Change Detection—0
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation—0
Free Supervision From Video Games—0
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments—0
Fruit Detection, Segmentation and 3D Visualisation of Environments in Apple Orchards—0
FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels—0
Fully-Automated Packaging Structure Recognition in Logistics Environments—0
GANtruth - an unpaired image-to-image translation method for driving scenarios—0
gen2seg: Generative Models Enable Generalizable Instance Segmentation—0
Generalized Class Discovery in Instance Segmentation—0
Generalized Mask-aware IoU for Anchor Assignment for Real-time Instance Segmentation—0
Generalized Object Detection on Fisheye Cameras for Autonomous Driving: Dataset, Representations and Baseline—0
Generative AI Driven Task-Oriented Adaptive Semantic Communications—0
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Gen-n-Val: Agentic Image Data Generation and Validation—0
Geometric Image Synthesis—0
Geometry-Aware Fruit Grasping Estimation for Robotic Harvesting in Orchards—0
Geomorphological Analysis Using Unpiloted Aircraft Systems, Structure from Motion, and Deep Learning—0
GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation—0
Gland Instance Segmentation by Deep Multichannel Side Supervision—0
Gland Instance Segmentation by Deep Multichannel Neural Networks—0
Gland Instance Segmentation Using Deep Multichannel Neural Networks—0
Global Collinearity-aware Polygonizer for Polygonal Building Mapping in Remote Sensing—0
Global Motion Understanding in Large-Scale Video Object Segmentation—0
GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation—0
GoodSAM++: Bridging Domain and Capacity Gaps via Segment Anything Model for Panoramic Semantic Segmentation—0
GP-NeRF: Generalized Perception NeRF for Context-Aware 3D Scene Understanding—0
Grafting Vision Transformers—0
GraphBGS: Background Subtraction via Recovery of Graph Signals—0
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos—0
Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects—0
Growing Instance Mask on Leaf—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