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 1901–1950 of 2262 papers

TitleStatusHype
X3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
X-volution: On the unification of convolution and self-attention—0
X-World: Accessibility, Vision, and Autonomy Meet—0
YOLO2U-Net: Detection-Guided 3D Instance Segmentation for Microscopy—0
You Only Click Once: Single Point Weakly Supervised 3D Instance Segmentation for Autonomous Driving—0
You Only Estimate Once: Unified, One-stage, Real-Time Category-level Articulated Object 6D Pose Estimation for Robotic Grasping—0
ZeroPS: High-quality Cross-modal Knowledge Transfer for Zero-Shot 3D Part Segmentation—0
Zero-Shot Anomaly Detection with Pre-trained Segmentation Models—0
Zero-Shot Automatic Annotation and Instance Segmentation using LLM-Generated Datasets: Eliminating Field Imaging and Manual Annotation for Deep Learning Model Development—0
Zero-Shot Dual-Path Integration Framework for Open-Vocabulary 3D Instance Segmentation—0
ZigZagNet: Fusing Top-Down and Bottom-Up Context for Object Segmentation—0
SSAP: Single-Shot Instance Segmentation With Affinity PyramidCode0
Image-based Detection of Surface Defects in Concrete during ConstructionCode0
XAMI -- A Benchmark Dataset for Artefact Detection in XMM-Newton Optical ImagesCode0
Conditional Negative Sampling for Contrastive Learning of Visual RepresentationsCode0
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature SpaceCode0
AdaptIS: Adaptive Instance Selection NetworkCode0
Unsupervised Anomaly Instance Segmentation for Baggage Threat RecognitionCode0
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language TasksCode0
IM2HEIGHT: Height Estimation from Single Monocular Imagery via Fully Residual Convolutional-Deconvolutional NetworkCode0
Straight to Shapes++: Real-time Instance Segmentation Made More AccurateCode0
AdaContour: Adaptive Contour Descriptor with Hierarchical RepresentationCode0
iFS-RCNN: An Incremental Few-shot Instance SegmenterCode0
Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the operating roomCode0
ColorMAE: Exploring data-independent masking strategies in Masked AutoEncodersCode0
COIN: Confidence Score-Guided Distillation for Annotation-Free Cell SegmentationCode0
Unsupervised object-centric video generation and decomposition in 3DCode0
Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple ObjectsCode0
ICDAR 2021 Competition on Historical Map SegmentationCode0
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
How Shift Equivariance Impacts Metric Learning for Instance SegmentationCode0
Weakly Supervised Instance Segmentation using Class Peak ResponseCode0
Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Point CloudsCode0
HistoNet: Predicting size histograms of object instancesCode0
Surgical fine-tuning for Grape Bunch Segmentation under Visual Domain ShiftsCode0
Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance SegmentationCode0
Hiera: A Hierarchical Vision Transformer without the Bells-and-WhistlesCode0
Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing ImageryCode0
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual RepresentationsCode0
HaDR: Applying Domain Randomization for Generating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial EnvironmentsCode0
Actor-Critic Instance SegmentationCode0
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance SegmentationCode0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
Grape detection, segmentation and tracking using deep neural networks and three-dimensional associationCode0
CoDA: Interactive Segmentation and Morphological Analysis of Dendroid Structures Exemplified on Stony Cold-Water CoralsCode0
Gramian Attention Heads are Strong yet Efficient Vision LearnersCode0
Weakly Supervised Instance Segmentation using the Bounding Box Tightness PriorCode0
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient ImagesCode0
GMT: Guided Mask Transformer for Leaf Instance SegmentationCode0
UPSNet: A Unified Panoptic Segmentation NetworkCode0
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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