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 851875 of 2262 papers

TitleStatusHype
Affinity Derivation and Graph Merge for Instance SegmentationCode0
Attention-Guided Residual U-Net with SE Connection and ASPP for Watershed-Based Cell Segmentation in Microscopy ImagesCode0
Rapid Automated Mapping of Clouds on Titan With Instance SegmentationCode0
A Feasible Framework for Arbitrary-Shaped Scene Text RecognitionCode0
Rain Removal in Traffic Surveillance: Does it Matter?Code0
RDCNet: Instance segmentation with a minimalist recurrent residual networkCode0
Conditional Negative Sampling for Contrastive Learning of Visual RepresentationsCode0
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware AssociationCode0
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual RepresentationsCode0
Relevance Attack on DetectorsCode0
PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical InstrumentsCode0
PyPotteryLens: An Open-Source Deep Learning Framework for Automated Digitisation of Archaeological Pottery DocumentationCode0
Prompting Vision-Language Model for Nuclei Instance Segmentation and ClassificationCode0
Pyramid Mask Text DetectorCode0
RDSNet: A New Deep Architecture for Reciprocal Object Detection and Instance SegmentationCode0
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance SegmentationCode0
Predicting Future Instance Segmentation by Forecasting Convolutional FeaturesCode0
PPR-Net:Point-wise Pose Regression Network for Instance Segmentation and 6D Pose Estimation in Bin-picking ScenariosCode0
PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and ClassificationCode0
HaDR: Applying Domain Randomization for Generating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial EnvironmentsCode0
Precise Location Matching Improves Dense Contrastive Learning in Digital PathologyCode0
Grape detection, segmentation and tracking using deep neural networks and three-dimensional associationCode0
Gramian Attention Heads are Strong yet Efficient Vision LearnersCode0
Pose2Seg: Detection Free Human Instance SegmentationCode0
Polyp-SES: Automatic Polyp Segmentation with Self-Enriched Semantic ModelCode0
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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