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 1451–1500 of 2262 papers

TitleStatusHype
A Benchmark of Long-tailed Instance Segmentation with Noisy LabelsCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?—0
Rethinking Implicit Neural Representations for Vision Learners—0
Task-Specific Data Augmentation and Inference Processing for VIPriors Instance Segmentation Challenge—0
The Runner-up Solution for YouTube-VIS Long Video Challenge 2022—0
SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification—0
3D-QueryIS: A Query-based Framework for 3D Instance Segmentation—0
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation—0
Label-Efficient Object Detection via Region Proposal Network Pre-Training—0
Robust Online Video Instance Segmentation with Track QueriesCode0
PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection—0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping—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
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
MR-NOM: Multi-scale Resolution of Neuronal cells in Nissl-stained histological slices via deliberate Over-segmentation and Merging—0
Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding—0
BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield imagesCode0
Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks—0
Could Giant Pretrained Image Models Extract Universal Representations?—0
Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach—0
CircleSnake: Instance Segmentation with Circle RepresentationCode0
Two-Level Temporal Relation Model for Online Video Instance SegmentationCode0
Grafting Vision Transformers—0
Layout Aware Inpainting for Automated Furniture Removal in Indoor Scenes—0
Cell tracking for live-cell microscopy using an activity-prioritized assignment strategyCode0
MGTUNet: An new UNet for colon nuclei instance segmentation and quantification—0
Comparative analysis of deep learning approaches for AgNOR-stained cytology samples interpretation—0
Deformably-Scaled Transposed Convolution—0
Instance Segmentation with Cross-Modal Consistency—0
Time-Space Transformers for Video Panoptic Segmentation—0
Domain Adaptation for Unknown Image Distortions in Instance Segmentation—0
K-means for unsupervised instance segmentation using a self-supervised transformer—0
Diversified Dynamic Routing for Vision Tasks—0
RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement—0
D-InLoc++: Indoor Localization in Dynamic EnvironmentsCode0
A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s AlphaCode0
SOCRATES: A Stereo Camera Trap for Monitoring of BiodiversityCode0
Inverse Image Frequency for Long-tailed Image RecognitionCode0
Self-supervised Learning for Panoptic Segmentation of Multiple Fruit Flower SpeciesCode0
Exploring Target Representations for Masked AutoencodersCode0
SUNet: Scale-aware Unified Network for Panoptic Segmentation—0
Automatic counting of mounds on UAV images: combining instance segmentation and patch-level correction—0
SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ Histopathology Image Synthesis—0
Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation—0
MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition—0
Nuclei & Glands Instance Segmentation in Histology Images: A Narrative Review—0
gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window—0
Weakly Supervised Airway Orifice Segmentation in Video Bronchoscopy—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