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 1–25 of 2262 papers

TitleStatusHype
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
No time to train! Training-Free Reference-Based Instance SegmentationCode3
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
The Four Color Theorem for Cell Instance SegmentationCode1
SAM2Auto: Auto Annotation Using FLASH—0
OpenSplat3D: Open-Vocabulary 3D Instance Segmentation using Gaussian Splatting—0
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping—0
Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagery—0
OpenMaskDINO3D : Reasoning 3D Segmentation via Large Language ModelCode1
Gen-n-Val: Agentic Image Data Generation and Validation—0
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx—0
SPPSFormer: High-quality Superpoint-based Transformer for Roof Plane Instance Segmentation from Point Clouds—0
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation—0
ConfLUNet: Multiple sclerosis lesion instance segmentation in presence of confluent lesions—0
The Missing Point in Vision Transformers for Universal Image SegmentationCode2
Show:102550
← PrevPage 1 of 91Next →

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