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 1251–1275 of 2262 papers

TitleStatusHype
All you need is a second look: Towards Tighter Arbitrary shape text detection—0
All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting—0
A Low Rank Promoting Prior for Unsupervised Contrastive Learning—0
A Manifold Representation of the Key in Vision Transformers—0
A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation—0
Amodal Instance Segmentation—0
Amodal Instance Segmentation with Diffusion Shape Prior Estimation—0
Amodal Panoptic Segmentation—0
Amodal segmentation just like doing a jigsaw—0
An annotated instance segmentation XXL-CT data-set from a historic airplane—0
An Efficient Instance Segmentation Approach for Extracting Fission Gas Bubbles on U-10Zr Annular Fuel—0
An Embedding-Dynamic Approach to Self-supervised Learning—0
An Empirical Study of Uncertainty in Polygon Annotation and the Impact of Quality Assurance—0
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians—0
A New Image Codec Paradigm for Human and Machine Uses—0
An Exemplar-based CRF for Multi-instance Object Segmentation—0
An Extendable, Efficient and Effective Transformer-based Object Detector—0
An Interpretable Deep Learning Approach for Morphological Script Type Analysis—0
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters—0
An Object Aware Hybrid U-Net for Breast Tumour Annotation—0
An object-centric sensitivity analysis of deep learning based instance segmentation—0
A novel integrated method of detection-grasping for specific object based on the box coordinate matching—0
A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images—0
A Novel WaveInst-based Network for Tree Trunk Structure Extraction and Pattern Analysis in Forest Inventory—0
Any3DIS: Class-Agnostic 3D Instance Segmentation by 2D Mask Tracking—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