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 851–900 of 2262 papers

TitleStatusHype
A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI—0
1st Place Solution for CVPR2023 BURST Long Tail and Open World Challenges—0
Automated Measurements of Key Morphological Features of Human Embryos for IVF—0
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey—0
A Histogram Thresholding Improvement to Mask R-CNN for Scalable Segmentation of New and Old Rural Buildings—0
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics—0
Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation—0
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds—0
AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model—0
A2VIS: Amodal-Aware Approach to Video Instance Segmentation—0
Joint 3D Instance Segmentation and Object Detection for Autonomous Driving—0
JSMNet Improving Indoor Point Cloud Semantic and Instance Segmentation through Self-Attention and Multiscale—0
Counting of Grapevine Berries in Images via Semantic Segmentation using Convolutional Neural Networks—0
A2-FPN: Attention Aggregation Based Feature Pyramid Network for Instance Segmentation—0
Counting and Segmenting Sorghum Heads—0
A Graph Matching Perspective With Transformers on Video Instance Segmentation—0
Iterative Instance Segmentation—0
Could Giant Pretrained Image Models Extract Universal Representations?—0
AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss—0
CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks—0
Aggregation With Feature Detection—0
Iterative Learning for Instance Segmentation—0
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning—0
Convolutional Neural Networks based automated segmentation and labelling of the lumbar spine X-ray—0
AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish—0
AutoBSS: An Efficient Algorithm for Block Stacking Style Search—0
3D for Free: Crossmodal Transfer Learning using HD Maps—0
A Unified Sequence Interface for Vision Tasks—0
A^2-FPN: Attention Aggregation based Feature Pyramid Network for Instance Segmentation—0
iShape: A First Step Towards Irregular Shape Instance Segmentation—0
Contrastive Learning for Automotive mmWave Radar Detection Points Based Instance Segmentation—0
ContourRender: Detecting Arbitrary Contour Shape For Instance Segmentation In One Pass—0
A Unified Interactive Model Evaluation for Classification, Object Detection, and Instance Segmentation in Computer Vision—0
Contour Loss for Instance Segmentation via k-step Distance Transformation Image—0
GASP, a generalized framework for agglomerative clustering of signed graphs and its application to Instance Segmentation—0
Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes—0
Continental-Scale Building Detection from High Resolution Satellite Imagery—0
Augment Before Copy-Paste: Data and Memory Efficiency-Oriented Instance Segmentation Framework for Sport-scenes—0
A Fully Unsupervised Instance Segmentation Technique for White Blood Cell Images—0
A2D2: Audi Autonomous Driving Dataset—0
Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation—0
Contextual Graph Reasoning Networks—0
Context-Preserving Instance-Level Augmentation and Deformable Convolution Networks for SAR Ship Detection—0
How Object Information Improves Skeleton-based Human Action Recognition in Assembly Tasks—0
AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation—0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?—0
How can we learn (more) from challenges? A statistical approach to driving future algorithm development—0
Content-Aware Multi-Level Guidance for Interactive Instance Segmentation—0
3D Feature Distillation with Object-Centric Priors—0
1% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions—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