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 1751–1800 of 2262 papers

TitleStatusHype
Deep Active Contours Using Locally Controlled Distance Vector Flow—0
Temporal Prediction and Evaluation of Brassica Growth in the Field using Conditional Generative Adversarial Networks—0
Instance Segmentation of Microscopic ForaminiferaCode0
A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation—0
Instance segmentation of fallen trees in aerial color infrared imagery using active multi-contour evolution with fully convolutional network-based intensity priors—0
ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception—0
Multimodal Contrastive Training for Visual Representation Learning—0
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos—0
Guided Table Structure Recognition through Anchor Optimization—0
Fashion-Guided Adversarial Attack on Person SegmentationCode0
Ridge Regression Neural Network for Pediatric Bone Age Assessment—0
Volume and leaf area calculation of cabbage with a neural network-based instance segmentation—0
A Reinforcement-Learning-Based Energy-Efficient Framework for Multi-Task Video Analytics Pipeline—0
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient ImagesCode0
DARCNN: Domain Adaptive Region-based Convolutional Neural Network forUnsupervised Instance Segmentation in Biomedical ImagesCode0
Recursively Refined R-CNN: Instance Segmentation with Self-RoI RebalancingCode0
DARCNN: Domain Adaptive Region-based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical ImagesCode0
Unsupervised Discovery of the Long-Tail in Instance Segmentation Using Hierarchical Self-Supervision—0
The surprising impact of mask-head architecture on novel class segmentationCode0
Learning to Track Instances without Video Annotations—0
Using depth information and colour space variations for improving outdoor robustness for instance segmentation of cabbage—0
Camouflaged Instance Segmentation In-The-Wild: Dataset, Method, and Benchmark Suite—0
Assessing YOLACT++ for real time and robust instance segmentation of medical instruments in endoscopic procedures—0
SIMstack: A Generative Shape and Instance Model for Unordered Object Stacks—0
PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN—0
Instance segmentation with the number of clusters incorporated in embedding learning—0
Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency—0
Dilated SpineNet for Semantic Segmentation—0
Human De-occlusion: Invisible Perception and Recovery for Humans—0
Generic Perceptual Loss for Modeling Structured Output Dependencies—0
Robust 2D/3D Vehicle Parsing in CVIS—0
Instance Segmentation GNNs for One-Shot Conformal Tracking at the LHC—0
Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually ImpairedCode0
SCD: A Stacked Carton Dataset for Detection and SegmentationCode0
SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences—0
Contour Loss for Instance Segmentation via k-step Distance Transformation Image—0
CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell Segmentation and Tracking in Microscopy ImagesCode0
One Shot Model For COVID-19 Classification and Lesions Segmentation In Chest CT Scans Using LSTM With Attention MechanismCode0
One Shot Model For COVID-19 Classification and Lesions Segmentation In Chest CT Scans Using LSTM With Attention MechanismCode0
EfficientLPS: Efficient LiDAR Panoptic Segmentation—0
Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework—0
INSTA-YOLO: Real-Time Instance Segmentation—0
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement—0
Exploiting Depth Information for Wildlife MonitoringCode0
3D Object Detection and Instance Segmentation from 3D Range and 2D Color Images—0
A Histogram Thresholding Improvement to Mask R-CNN for Scalable Segmentation of New and Old Rural Buildings—0
Instance and Panoptic Segmentation Using Conditional Convolutions—0
Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement—0
Nondiscriminatory Treatment: a straightforward framework for multi-human parsing—0
Self-Supervised Representation Learning from Flow Equivariance—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