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 18011850 of 2262 papers

TitleStatusHype
Boundary-assisted Region Proposal Networks for Nucleus SegmentationCode1
DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous ConvolutionCode2
Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set0
D2Det: Towards High Quality Object Detection and Instance SegmentationCode1
Density-Based Clustering for 3D Object Detection in Point Clouds0
Improving Convolutional Networks With Self-Calibrated ConvolutionsCode1
End-to-End 3D Point Cloud Instance Segmentation Without Detection0
3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance SegmentationCode1
Video Instance Segmentation Tracking With a Modified VAE Architecture0
TESA: Tensor Element Self-Attention via Matricization0
Joint 3D Instance Segmentation and Object Detection for Autonomous Driving0
CenterMask: Real-Time Anchor-Free Instance SegmentationCode1
Deep Polarization Cues for Transparent Object Segmentation0
3D Part Guided Image Editing for Fine-Grained Object UnderstandingCode1
Learning Saliency Propagation for Semi-Supervised Instance SegmentationCode1
Interactive Object Segmentation With Inside-Outside GuidanceCode1
NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy ImagesCode1
Automated Measurements of Key Morphological Features of Human Embryos for IVF0
Poly-YOLO: higher speed, more precise detection and instance segmentation for YOLOv3Code1
NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisationCode1
AutoSweep: Recovering 3D Editable Objectsfrom a Single PhotographCode1
On Mutual Information in Contrastive Learning for Visual Representations0
An interpretable automated detection system for FISH-based HER2 oncogene amplification testing in histo-pathological routine images of breast and gastric cancer diagnosticsCode0
Attention-guided Context Feature Pyramid Network for Object DetectionCode1
Panoptic Instance Segmentation on Pigs0
Towards Streaming PerceptionCode1
What Makes for Good Views for Contrastive Learning?0
Self-supervised Transfer Learning for Instance Segmentation through Physical InteractionCode0
Reinforced Coloring for End-to-End Instance Segmentation0
Multi-Task Learning in Histo-pathology for Widely Generalizable Model0
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance SegmentationCode1
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weightingCode1
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks0
A novel Region of Interest Extraction Layer for Instance SegmentationCode0
Dynamic Scale Training for Object DetectionCode1
All you need is a second look: Towards Tighter Arbitrary shape text detection0
Fashionpedia: Ontology, Segmentation, and an Attribute Localization DatasetCode1
Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local ConstraintsCode1
ResNeSt: Split-Attention NetworksCode3
MOPT: Multi-Object Panoptic Tracking0
A Transductive Approach for Video Object SegmentationCode1
Bidirectional Graph Reasoning Network for Panoptic Segmentation0
A2D2: Audi Autonomous Driving Dataset0
CenterMask: single shot instance segmentation with point representation0
Evolving Normalization-Activation LayersCode1
EfficientPS: Efficient Panoptic SegmentationCode1
Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray0
Pixel Consensus Voting for Panoptic Segmentation0
PointGroup: Dual-Set Point Grouping for 3D Instance SegmentationCode1
Look-into-Object: Self-supervised Structure Modeling for Object RecognitionCode1
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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