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 5175 of 2262 papers

TitleStatusHype
NVSMask3D: Hard Visual Prompting with Camera Pose Interpolation for 3D Open Vocabulary Instance Segmentation0
Occlusion-Ordered Semantic Instance Segmentation0
Single-shot Star-convex Polygon-based Instance Segmentation for Spatially-correlated Biomedical Objects0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting0
CAP-Net: A Unified Network for 6D Pose and Size Estimation of Categorical Articulated Parts from a Single RGB-D Image0
Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data GenerationCode0
P2Object: Single Point Supervised Object Detection and Instance SegmentationCode2
Wheat3DGS: In-field 3D Reconstruction, Instance Segmentation and Phenotyping of Wheat Heads with Gaussian SplattingCode1
S^4M: Boosting Semi-Supervised Instance Segmentation with SAM0
BoxSeg: Quality-Aware and Peer-Assisted Learning for Box-supervised Instance SegmentationCode0
APSeg: Auto-Prompt Model with Acquired and Injected Knowledge for Nuclear Instance Segmentation and Classification0
Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite ImageryCode2
Rip Current Segmentation: A Novel Benchmark and YOLOv8 Baseline ResultsCode1
Scene-Centric Unsupervised Panoptic SegmentationCode2
Instance Migration Diffusion for Nuclear Instance Segmentation in Pathology0
v-CLR: View-Consistent Learning for Open-World Instance SegmentationCode1
CellVTA: Enhancing Vision Foundation Models for Accurate Cell Segmentation and ClassificationCode1
RipVIS: Rip Currents Video Instance Segmentation Benchmark for Beach Monitoring and Safety0
Pre-training with 3D Synthetic Data: Learning 3D Point Cloud Instance Segmentation from 3D Synthetic Scenes0
Foveated Instance SegmentationCode0
Prompting Vision-Language Model for Nuclei Instance Segmentation and ClassificationCode0
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery0
Multiscale Feature Importance-based Bit Allocation for End-to-End Feature Coding for Machines0
EgoSurgery-HTS: A Dataset for Egocentric Hand-Tool Segmentation in Open Surgery VideosCode0
HiRes-FusedMIM: A High-Resolution RGB-DSM Pre-trained Model for Building-Level Remote Sensing Applications0
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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