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 101–150 of 2262 papers

TitleStatusHype
You Only Click Once: Single Point Weakly Supervised 3D Instance Segmentation for Autonomous Driving—0
OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic KernelsCode4
CLIMB-3D: Continual Learning for Imbalanced 3D Instance SegmentationCode0
DAMamba: Vision State Space Model with Dynamic Adaptive ScanCode2
WeedsGalore: A Multispectral and Multitemporal UAV-based Dataset for Crop and Weed Segmentation in Agricultural Maize FieldsCode1
Leveraging Multimodal-LLMs Assisted by Instance Segmentation for Intelligent Traffic Monitoring—0
FrGNet: A fourier-guided weakly-supervised framework for nuclear instance segmentationCode0
Instance Segmentation of Scene Sketches Using Natural Image Priors—0
HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and ClassificationCode1
Generalized Class Discovery in Instance Segmentation—0
VFX Creator: Animated Visual Effect Generation with Controllable Diffusion Transformer—0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers—0
Beyond the Final Layer: Hierarchical Query Fusion Transformer with Agent-Interpolation Initialization for 3D Instance Segmentation—0
Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning DynamicsCode1
ZISVFM: Zero-Shot Object Instance Segmentation in Indoor Robotic Environments with Vision Foundation ModelsCode0
Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation—0
Mind the Gap: Evaluating Patch Embeddings from General-Purpose and Histopathology Foundation Models for Cell Segmentation and ClassificationCode1
Memory Efficient Transformer Adapter for Dense Predictions—0
Segment Anything for HistopathologyCode2
Lifting by Gaussians: A Simple, Fast and Flexible Method for 3D Instance Segmentation—0
INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation—0
Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations—0
ContourFormer:Real-Time Contour-Based End-to-End Instance Segmentation TransformerCode1
D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation—0
iFormer: Integrating ConvNet and Transformer for Mobile ApplicationCode2
Vision Aided Channel Prediction for Vehicular Communications: A Case Study of Received Power Prediction Using RGB Images—0
Effective Defect Detection Using Instance Segmentation for NDI—0
ENSeg: A Novel Dataset and Method for the Segmentation of Enteric Neuron Cells on Microscopy ImagesCode0
LiCAR: pseudo-RGB LiDAR image for CAR segmentation—0
Foreign object segmentation in chest x-rays through anatomy-guided shape insertion—0
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision—0
Advancing Oyster Phenotype Segmentation with Multi-Network Ensemble and Multi-Scale mechanism—0
ClusterViG: Efficient Globally Aware Vision GNNs via Image Partitioning—0
SmartEraser: Remove Anything from Images using Masked-Region Guidance—0
TimberVision: A Multi-Task Dataset and Framework for Log-Component Segmentation and Tracking in Autonomous Forestry OperationsCode1
Toward Realistic Camouflaged Object Detection: Benchmarks and MethodCode1
Static Segmentation by Tracking: A Frustratingly Label-Efficient Approach to Fine-Grained Segmentation—0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
Rapid Automated Mapping of Clouds on Titan With Instance SegmentationCode0
AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish—0
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
Dedicated Inference Engine and Binary-Weight Neural Networks for Lightweight Instance Segmentation—0
Efficient Connectivity-Preserving Instance Segmentation with Supervoxel-Based Loss FunctionCode1
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
Minimizing Labeled, Maximizing Unlabeled: An Image-Driven Approach for Video Instance Segmentation—0
Advancing Manga Analysis: Comprehensive Segmentation Annotations for the Manga109 Dataset—0
Relation3D : Enhancing Relation Modeling for Point Cloud Instance SegmentationCode1
SAM2Object: Consolidating View Consistency via SAM2 for Zero-Shot 3D Instance Segmentation—0
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature SpaceCode0
WISH: Weakly Supervised Instance Segmentation using Heterogeneous Labels—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