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 951–1000 of 2262 papers

TitleStatusHype
Deep learning approaches to building rooftop thermal bridge detection from aerial imagesCode1
Test-time Adaptation vs. Training-time Generalization: A Case Study in Human Instance Segmentation using Keypoints Estimation—0
Robust Perception through EquivarianceCode0
Benchmarking Self-Supervised Learning on Diverse Pathology DatasetsCode1
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusionCode1
AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentation—0
LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous DrivingCode1
MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality MicroscopyCode1
Framework-agnostic Semantically-aware Global Reasoning for Segmentation—0
Iterative Next Boundary Detection for Instance Segmentation of Tree Rings in Microscopy Images of Shrub Cross SectionsCode1
DiffusionInst: Diffusion Model for Instance SegmentationCode2
Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query EmbeddingCode1
Box2Mask: Box-supervised Instance Segmentation via Level-set EvolutionCode2
3D Segmentation of Humans in Point Clouds with Synthetic Data—0
Uncertainty-Aware Contour Proposal Networks for Cell Segmentation in Multi-Modality High-Resolution Microscopy ImagesCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
Growing Instance Mask on Leaf—0
PLA: Language-Driven Open-Vocabulary 3D Scene UnderstandingCode2
Superpoint Transformer for 3D Scene Instance SegmentationCode1
FsaNet: Frequency Self-attention for Semantic SegmentationCode1
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments—0
EasyMLServe: Easy Deployment of REST Machine Learning ServicesCode0
Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation—0
Language-Assisted 3D Feature Learning for Semantic Scene UnderstandingCode1
A Benchmark of Long-tailed Instance Segmentation with Noisy LabelsCode0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?—0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
DETRs with Collaborative Hybrid Assignments TrainingCode3
Rethinking Implicit Neural Representations for Vision Learners—0
Task-Specific Data Augmentation and Inference Processing for VIPriors Instance Segmentation Challenge—0
Mean Shift Mask Transformer for Unseen Object Instance SegmentationCode1
PIDray: A Large-scale X-ray Benchmark for Real-World Prohibited Item DetectionCode1
SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification—0
The Runner-up Solution for YouTube-VIS Long Video Challenge 2022—0
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation—0
3D-QueryIS: A Query-based Framework for 3D Instance Segmentation—0
A Generalized Framework for Video Instance SegmentationCode1
Robust Online Video Instance Segmentation with Track QueriesCode0
Label-Efficient Object Detection via Region Proposal Network Pre-Training—0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping—0
PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection—0
Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System—0
Recursive Cross-View: Use Only 2D Detectors to Achieve 3D Object Detection without 3D Annotations—0
MR-NOM: Multi-scale Resolution of Neuronal cells in Nissl-stained histological slices via deliberate Over-segmentation and Merging—0
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
OneFormer: One Transformer to Rule Universal Image SegmentationCode3
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable ConvolutionsCode4
Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding—0
MogaNet: Multi-order Gated Aggregation NetworkCode2
BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield imagesCode0
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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