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 801–850 of 2262 papers

TitleStatusHype
MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAMCode1
GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point CloudCode1
Efficient Attention: Attention with Linear ComplexitiesCode1
One-Shot Instance SegmentationCode1
Deformable ConvNets v2: More Deformable, Better ResultsCode1
Weakly- and Semi-Supervised Panoptic SegmentationCode1
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
The ApolloScape Open Dataset for Autonomous Driving and its ApplicationCode1
Path Aggregation Network for Instance SegmentationCode1
Multiclass Weighted Loss for Instance Segmentation of Cluttered CellsCode1
Panoptic SegmentationCode1
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANsCode1
Non-local Neural NetworksCode1
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and SemanticsCode1
Mask R-CNNCode1
Microsoft COCO: Common Objects in ContextCode1
SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance SegmentationCode0
Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping—0
SPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning—0
DreamGrasp: Zero-Shot 3D Multi-Object Reconstruction from Partial-View Images for Robotic Manipulation—0
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation—0
NOCTIS: Novel Object Cyclic Threshold based Instance SegmentationCode0
VoteSplat: Hough Voting Gaussian Splatting for 3D Scene Understanding—0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—0
Prohibited Items Segmentation via Occlusion-aware Bilayer ModelingCode0
ALBERT: Advanced Localization and Bidirectional Encoder Representations from Transformers for Automotive Damage Evaluation—0
Accurate and efficient zero-shot 6D pose estimation with frozen foundation models—0
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting—0
SAM2Auto: Auto Annotation Using FLASH—0
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping—0
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx—0
Gen-n-Val: Agentic Image Data Generation and Validation—0
Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery—0
SPPSFormer: High-quality Superpoint-based Transformer for Roof Plane Instance Segmentation from Point Clouds—0
ConfLUNet: Multiple sclerosis lesion instance segmentation in presence of confluent lesions—0
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation—0
ThinkVideo: High-Quality Reasoning Video Segmentation with Chain of ThoughtsCode0
Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting—0
gen2seg: Generative Models Enable Generalizable Instance Segmentation—0
Instance Segmentation for Point Sets—0
FlowCut: Unsupervised Video Instance Segmentation via Temporal Mask Matching—0
Industrial Synthetic Segment Pre-training—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
SoftPQ: Robust Instance Segmentation Evaluation via Soft Matching and Tunable ThresholdsCode0
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision—0
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation—0
The RaspGrade Dataset: Towards Automatic Raspberry Ripeness Grading with Deep Learning—0
Vision Foundation Model Embedding-Based Semantic Anomaly Detection—0
Mix-QSAM: Mixed-Precision Quantization of the Segment Anything Model—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
8GLEE-Promask AP54.2—Unverified
9ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2—Unverified
10SwinV2-G (HTC++)mask AP53.7—Unverified