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 19261950 of 2262 papers

TitleStatusHype
Real-Time Fruit Recognition and Grasping Estimation for Autonomous Apple Harvesting0
Spatial Attention Pyramid Network for Unsupervised Domain Adaptation0
Mask Encoding for Single Shot Instance Segmentation0
Robust Medical Instrument Segmentation Challenge 20190
Neural Mesh Refiner for 6-DoF Pose Estimation0
Deep Affinity Net: Instance Segmentation via Affinity0
OccuSeg: Occupancy-aware 3D Instance Segmentation0
PointINS: Point-based Instance Segmentation0
A Convolutional Neural Network for Point Cloud Instance Segmentation in Cluttered Scene Trained by Synthetic Data Without Color0
A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI0
FLIC: Fast Lidar Image Clustering0
3DCFS: Fast and Robust Joint 3D Semantic-Instance Segmentation via Coupled Feature Selection0
Towards Bounding-Box Free Panoptic Segmentation0
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians0
Layered Embeddings for Amodal Instance SegmentationCode0
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation0
Weakly Supervised Instance Segmentation by Deep Community Learning0
Virtual KITTI 20
Accurately identifying vertebral levels in large datasets0
SDOD:Real-time Segmenting and Detecting 3D Object by Depth0
Instance Segmentation of Visible and Occluded Regions for Finding and Picking Target from a Pile of Objects0
Joint Learning of Instance and Semantic Segmentation for Robotic Pick-and-Place with Heavy Occlusions in Clutter0
GraphBGS: Background Subtraction via Recovery of Graph Signals0
Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey0
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark0
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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