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

Showing 13011325 of 2262 papers

TitleStatusHype
Attention-based Feature Aggregation0
AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation0
Augment Before Copy-Paste: Data and Memory Efficiency-Oriented Instance Segmentation Framework for Sport-scenes0
Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes0
A Unified Interactive Model Evaluation for Classification, Object Detection, and Instance Segmentation in Computer Vision0
A Unified Sequence Interface for Vision Tasks0
AutoBSS: An Efficient Algorithm for Block Stacking Style Search0
AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish0
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey0
Automated Measurements of Key Morphological Features of Human Embryos for IVF0
Automated National Urban Map Extraction0
Automatic Animation of Hair Blowing in Still Portrait Photos0
Automatic Cadastral Boundary Detection of Very High Resolution Images Using Mask R-CNN0
Automatic characterization of boulders on planetary surfaces from high-resolution satellite images0
Automatic counting of mounds on UAV images: combining instance segmentation and patch-level correction0
Automatic Drywall Analysis for Progress Tracking and Quality Control in Construction0
Automatic occlusion removal from 3D maps for maritime situational awareness0
Automatic Video Object Segmentation via Motion-Appearance-Stream Fusion and Instance-aware Segmentation0
Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation0
Automating lichen monitoring in ecological studies using instance segmentation of time-lapse images0
Automotive Parts Assessment: Applying Real-time Instance-Segmentation Models to Identify Vehicle Parts0
Autonomous Quilt Spreading for Caregiving Robots0
A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track0
A Weakly Supervised Method for Instance Segmentation of Biological Cells0
Base Layer Efficiency in Scalable Human-Machine Coding0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8Unverified
2ResNeSt-200 (multi-scale)AP5070.2Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8Unverified
5Co-DETRmask AP57.1Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1Unverified
7ISDA (ResNet-50)APL55.7Unverified
8EVAmask AP55.5Unverified
9FD-SwinV2-Gmask AP55.4Unverified
10Mask Frozen-DETRmask AP55.3Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501Unverified
2Co-DETRmask AP56.6Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9Unverified
4InternImage-Hmask AP55.4Unverified
5EVAmask AP55Unverified
6Mask Frozen-DETRmask AP54.9Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2Unverified
9GLEE-Promask AP54.2Unverified
10SwinV2-G (HTC++)mask AP53.7Unverified