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 1101–1150 of 2262 papers

TitleStatusHype
Neural Groundplans: Persistent Neural Scene Representations from a Single Image—0
In Defense of Online Models for Video Instance SegmentationCode2
NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds—0
Box-supervised Instance Segmentation with Level Set EvolutionCode2
Vision Transformers: From Semantic Segmentation to Dense PredictionCode3
KinD-LCE Curve Estimation And Retinex Fusion On Low-Light Image—0
Self-Supervised Interactive Object Segmentation Through a Singulation-and-Grasping Approach—0
3D Instances as 1D KernelsCode1
Graph CNN for Moving Object Detection in Complex Environments from Unseen Videos—0
3D Concept Grounding on Neural Fields—0
YOLO2U-Net: Detection-Guided 3D Instance Segmentation for Microscopy—0
Online Video Instance Segmentation via Robust Context Fusion—0
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation LearningCode2
Efficient Multi-Task RGB-D Scene Analysis for Indoor EnvironmentsCode1
A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation—0
An Embedding-Dynamic Approach to Self-supervised Learning—0
OSFormer: One-Stage Camouflaged Instance Segmentation with TransformersCode1
Vision-based Uneven BEV Representation Learning with Polar Rasterization and Surface EstimationCode1
Segmenting Moving Objects via an Object-Centric Layered RepresentationCode1
Beyond mAP: Towards better evaluation of instance segmentation—0
Domain Adaptive Nuclei Instance Segmentation and Classification via Category-aware Feature Alignment and Pseudo-labelling—0
A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction—0
BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR—0
InsMix: Towards Realistic Generative Data Augmentation for Nuclei Instance SegmentationCode0
UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer via Hierarchical Mask Calibration—0
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid NetworkCode1
Learn Fast, Segment Well: Fast Object Segmentation Learning on the iCub RobotCode1
PST: Plant segmentation transformer for 3D point clouds of rapeseed plants at the podding stage—0
Parallel Pre-trained Transformers (PPT) for Synthetic Data-based Instance Segmentation—0
Broken News: Making Newspapers Accessible to Print-Impaired—0
LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation—0
Global Context Vision TransformersCode2
Patch-level Representation Learning for Self-supervised Vision TransformersCode1
A Unified Sequence Interface for Vision Tasks—0
Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images—0
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation—0
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey—0
Consistent Video Instance Segmentation with Inter-Frame Recurrent Attention—0
RF-Next: Efficient Receptive Field Search for Convolutional Neural NetworksCode1
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics—0
GLIPv2: Unifying Localization and Vision-Language UnderstandingCode4
BFS-Net: Weakly Supervised Cell Instance Segmentation from Bright-Field Microscopy Z-Stacks—0
VITA: Video Instance Segmentation via Object Token AssociationCode1
SHRED: 3D Shape Region Decomposition with Learned Local OperationsCode1
Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and SegmentationCode4
Occlusion-Resistant Instance Segmentation of Piglets in Farrowing Pens Using Center Clustering Network—0
Metrics reloaded: Recommendations for image analysis validationCode1
Robustness Evaluation and Adversarial Training of an Instance Segmentation Model—0
What Are Expected Queries in End-to-End Object Detection?Code2
H-EMD: A Hierarchical Earth Mover's Distance Method for 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