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 1351–1400 of 2262 papers

TitleStatusHype
Pixel-Level Analysis for Enhancing Threat Detection in Large-Scale X-ray Security ImagesCode0
PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and ClassificationCode1
TA-Net: Topology-Aware Network for Gland Segmentation—0
A Survey of Self-Supervised and Few-Shot Object DetectionCode1
HR-RCNN: Hierarchical Relational Reasoning for Object Detection—0
hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries—0
Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer AggregationCode1
UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place SolutionCode1
CeyMo: See More on Roads -- A Novel Benchmark Dataset for Road Marking DetectionCode1
PlaneRecNet: Multi-Task Learning with Cross-Task Consistency for Piece-Wise Plane Detection and Reconstruction from a Single RGB ImageCode1
Multi-Object Tracking and Segmentation with a Space-Time Memory Network—0
Video Instance Segmentation by Instance Flow Assembly—0
1st Place Solution for the UVO Challenge on Image-based Open-World Segmentation 2021Code1
Mask-aware IoU for Anchor Assignment in Real-time Instance SegmentationCode1
The Aircraft Context Dataset: Understanding and Optimizing Data Variability in Aerial DomainsCode1
Accurate Fine-grained Layout Analysis for the Historical Tibetan Document Based on the Instance SegmentationCode0
Learning to Infer Kinematic Hierarchies for Novel Object Instances—0
High-throughput Phenotyping of Nematode Cysts—0
RoadObstacle21—0
Clustering Plotted Data by Image SegmentationCode1
Long-tailed Distribution AdaptationCode1
Deep Instance Segmentation with Automotive Radar Detection Points—0
Transformer Assisted Convolutional Network for Cell Instance SegmentationCode1
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk ControlCode1
MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation—0
Instance Segmentation Challenge Track Technical Report, VIPriors Workshop at ICCV 2021: Task-Specific Copy-Paste Data Augmentation Method for Instance SegmentationCode1
3rd Place Scheme on Instance Segmentation Track of ICCV 2021 VIPriors Challenges—0
Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images—0
iShape: A First Step Towards Irregular Shape Instance Segmentation—0
An object-centric sensitivity analysis of deep learning based instance segmentation—0
Attention-based Feature Aggregation—0
FoxInst: A Frustratingly Simple Baseline for Weakly Few-shot Instance Segmentation—0
Image BERT Pre-training with Online Tokenizer—0
Deep Structured Instance Graph for Distilling Object DetectorsCode1
TreeNet: A lightweight One-Shot Aggregation Convolutional Network—0
Localizing Infinity-shaped fishes: Sketch-guided object localization in the wildCode0
LGD: Label-guided Self-distillation for Object DetectionCode1
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion ModelingCode1
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-RefinementCode1
Dense Semantic Contrast for Self-Supervised Visual Representation Learning—0
UCP-Net: Unstructured Contour Points for Instance Segmentation—0
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
Temporal RoI Align for Video Object Recognition—0
Mask is All You Need: Rethinking Mask R-CNN for Dense and Arbitrary-Shaped Scene Text Detection—0
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with TransformersCode1
RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditions—0
RAMA: A Rapid Multicut Algorithm on GPUCode1
Benchmarking the Robustness of Instance Segmentation Models—0
Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasia—0
InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images—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