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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1601–1650 of 2262 papers

TitleStatusHype
INSTA-YOLO: Real-Time Instance Segmentation—0
Exploiting Depth Information for Wildlife MonitoringCode0
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement—0
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
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection ConsistencyCode1
Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement—0
Occluded Video Instance Segmentation: A BenchmarkCode1
SA-Net: Shuffle Attention for Deep Convolutional Neural NetworksCode1
Bottleneck Transformers for Visual RecognitionCode2
Nondiscriminatory Treatment: a straightforward framework for multi-human parsing—0
Embedding-based Instance Segmentation in MicroscopyCode1
Simplifying Object Segmentation with PixelLib LibraryCode2
Self-Supervised Representation Learning from Flow Equivariance—0
How Shift Equivariance Impacts Metric Learning for Instance SegmentationCode0
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized LabelsCode1
Superpixel-based Refinement for Object Proposal GenerationCode1
One Shot Model For The Prediction of COVID-19 and Lesions Segmentation In Chest CT Scans Through The Affinity Among Lesion Mask FeaturesCode0
ASIST: Annotation-free Synthetic Instance Segmentation and Tracking by Adversarial Simulations—0
Weakly Supervised Multi-Object Tracking and Segmentation—0
CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological ImagesCode1
Continuous Copy-Paste for One-Stage Multi-Object Tracking and SegmentationCode1
CDNet: Centripetal Direction Network for Nuclear Instance SegmentationCode1
Poly-NL: Linear Complexity Non-Local Layers With 3rd Order Polynomials—0
Robust 2D/3D Vehicle Parsing in Arbitrary Camera Views for CVISCode0
Aggregation With Feature Detection—0
PrimitiveNet: Primitive Instance Segmentation With Local Primitive Embedding Under Adversarial MetricCode1
Parallel Detection-and-Segmentation Learning for Weakly Supervised Instance Segmentation—0
X-World: Accessibility, Vision, and Autonomy Meet—0
AggMask: Exploring locally aggregated learning of mask representations for instance segmentationCode1
Learning a unified label space—0
EMPIRICAL UPPER BOUND IN OBJECT DETECTION—0
Contextual Graph Reasoning Networks—0
Inception Convolution with Efficient Dilation SearchCode1
Instance Segmentation of Industrial Point Cloud Data—0
Global Context NetworksCode2
SWA Object DetectionCode1
FcaNet: Frequency Channel Attention NetworksCode1
YolactEdge: Real-time Instance Segmentation on the EdgeCode2
Multiple Instance Segmentation in Brachial Plexus Ultrasound Image Using BPMSegNet—0
SCNet: Training Inference Sample Consistency for Instance SegmentationCode1
A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection—0
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene ContextsCode1
REFINE: Prediction Fusion Network for Panoptic Segmentation—0
Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object DetectionCode1
Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data AugmentationCode1
DeepGamble: Towards unlocking real-time player intelligence using multi-layer instance segmentation and attribute detection—0
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty EstimatesCode0
Simple Copy-Paste is a Strong Data Augmentation Method for Instance SegmentationCode1
Show:102550
← PrevPage 33 of 46Next →
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
8GLEE-Promask AP54.2—Unverified
9ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2—Unverified
10SwinV2-G (HTC++)mask AP53.7—Unverified