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 15511575 of 2262 papers

TitleStatusHype
Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds0
Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation0
Parallel Detection-and-Segmentation Learning for Weakly Supervised Instance Segmentation0
Parallel Pre-trained Transformers (PPT) for Synthetic Data-based Instance Segmentation0
ParFormer: A Vision Transformer with Parallel Mixer and Sparse Channel Attention Patch Embedding0
Paris-CARLA-3D: A Real and Synthetic Outdoor Point Cloud Dataset for Challenging Tasks in 3D Mapping0
Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning0
Perceive, Excavate and Purify: A Novel Object Mining Framework for Instance Segmentation0
Performance Evaluation of Segment Anything Model with Variational Prompting for Application to Non-Visible Spectrum Imagery0
Performance Evaluation of YOLOv8 Model Configurations, for Instance Segmentation of Strawberry Fruit Development Stages in an Open Field Environment0
Periodontal Bone Loss Analysis via Keypoint Detection With Heuristic Post-Processing0
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving0
Pixel Consensus Voting for Panoptic Segmentation0
Pixel-level Encoding and Depth Layering for Instance-level Semantic Labeling0
PlaneSAM: Multimodal Plane Instance Segmentation Using the Segment Anything Model0
PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN0
Playing for Benchmarks0
PLUTO: Pathology-Universal Transformer0
PMODE: Prototypical Mask based Object Dimension Estimation0
PM-VIS: High-Performance Box-Supervised Video Instance Segmentation0
Point2Mask: A Weakly Supervised Approach for Cell Segmentation Using Point Annotation0
Point2Tree(P2T) -- framework for parameter tuning of semantic and instance segmentation used with mobile laser scanning data in coniferous forest0
Point Cloud Instance Segmentation using Probabilistic Embeddings0
PointINS: Point-based Instance Segmentation0
PointInst3D: Segmenting 3D Instances by Points0
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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