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

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Showing 1851–1900 of 2262 papers

TitleStatusHype
RDCNet: Instance segmentation with a minimalist recurrent residual networkCode0
DOT: Dynamic Object Tracking for Visual SLAM—0
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation—0
Trainable Structure Tensors for Autonomous Baggage Threat Detection Under Extreme OcclusionCode0
Curriculum Learning with Diversity for Supervised Computer Vision Tasks—0
3D-FUTURE: 3D Furniture shape with TextURE—0
Proposal-Free Volumetric Instance Segmentation from Latent Single-Instance Masks—0
Channel-wise Alignment for Adaptive Object Detection—0
1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask—0
Fast Single-shot Ship Instance Segmentation Based on Polar Template Mask in Remote Sensing Images—0
Mask-guided sample selection for Semi-Supervised Instance Segmentation—0
Probabilistic Deep Learning for Instance Segmentation—0
3D for Free: Crossmodal Transfer Learning using HD Maps—0
Towards Autonomous Driving: a Multi-Modal 360^ Perception Proposal—0
Salient Instance Segmentation with Region and Box-level Annotations—0
Relevance Attack on DetectorsCode0
Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline—0
Fully-Automated Packaging Structure Recognition in Logistics Environments—0
LoCo: Local Contrastive Representation Learning—0
Joint Object Contour Points and Semantics for Instance Segmentation—0
Count- and Similarity-aware R-CNN for Pedestrian DetectionCode0
Learning Object Placement by Inpainting for Compositional Data Augmentation—0
Instance-Aware Embedding for Point Cloud Instance Segmentation—0
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
LevelSet R-CNN: A Deep Variational Method for Instance Segmentation—0
Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds—0
Instance-aware Self-supervised Learning for Nuclei Segmentation—0
Darwin's Neural Network: AI-based Strategies for Rapid and Scalable Cell and Coronavirus Screening—0
Split and Expand: An inference-time improvement for Weakly Supervised Cell Instance Segmentation—0
Can we cover navigational perception needs of the visually impaired by panoptic segmentation?—0
Feature Pyramid Transformer—0
Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances—0
CASNet: Common Attribute Support Network for image instance and panoptic segmentation—0
PerMO: Perceiving More at Once from a Single Image for Autonomous Driving—0
TrashCan: A Semantically-Segmented Dataset towards Visual Detection of Marine Debris—0
Unsupervised Spatio-temporal Latent Feature Clustering for Multiple-object Tracking and SegmentationCode0
Improving Pixel Embedding Learning through Intermediate Distance Regression Supervision for Instance Segmentation—0
Instance Segmentation for Whole Slide Imaging: End-to-End or Detect-Then-SegmentCode0
Unsupervised object-centric video generation and decomposition in 3DCode0
Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers—0
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition—0
A Survey on Instance Segmentation: State of the art—0
SASO: Joint 3D Semantic-Instance Segmentation via Multi-scale Semantic Association and Salient Point Clustering Optimization—0
NINEPINS: Nuclei Instance Segmentation with Point Annotations—0
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB—0
Geometry-Aware Instance Segmentation with Disparity MapsCode0
Instance segmentation of buildings using keypoints—0
Density-Based Clustering for 3D Object Detection in Point Clouds—0
Video Instance Segmentation Tracking With a Modified VAE Architecture—0
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All datasetsCOCO test-devCOCO minivalLVIS v1.0 valCityscapes valADE20K valARMBenchOccluded COCOOoDISSeparated COCOTBBRBDD100K valCOCO val (panoptic labels)

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
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2—Unverified
9GLEE-Promask AP54.2—Unverified
10SwinV2-G (HTC++)mask AP53.7—Unverified