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

Showing 251275 of 2262 papers

TitleStatusHype
Improving Weakly-supervised Video Instance Segmentation by Leveraging Spatio-temporal ConsistencyCode1
DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries0
InstanSeg: an embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentationCode3
Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation0
A Survey of Camouflaged Object Detection and BeyondCode3
Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping0
A Brief Analysis of the Iterative Next Boundary Detection Network for Tree Rings Delineation in Images of Pinus taedaCode0
Image Segmentation in Foundation Model Era: A SurveyCode2
Symmetric masking strategy enhances the performance of Masked Image Modeling0
ISETHDR: A Physics-based Synthetic Radiance Dataset for High Dynamic Range Driving ScenesCode1
NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei SegmentationCode1
EmbodiedSAM: Online Segment Any 3D Thing in Real TimeCode4
Open-Ended 3D Point Cloud Instance Segmentation0
An Interpretable Deep Learning Approach for Morphological Script Type Analysis0
Vocabulary-Free 3D Instance Segmentation with Vision and Language Assistant0
LSVOS Challenge 3rd Place Report: SAM2 and Cutie based VOS0
Leveraging Superfluous Information in Contrastive Representation Learning0
3D-Aware Instance Segmentation and Tracking in Egocentric Videos0
GoodSAM++: Bridging Domain and Capacity Gaps via Segment Anything Model for Panoramic Semantic Segmentation0
Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentation0
Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs0
Zero-Shot Dual-Path Integration Framework for Open-Vocabulary 3D Instance Segmentation0
5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition TasksCode3
Performance Evaluation of YOLOv8 Model Configurations, for Instance Segmentation of Strawberry Fruit Development Stages in an Open Field Environment0
Assessment of Cell Nuclei AI Foundation Models in Kidney PathologyCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8Unverified
2ResNeSt-200 (multi-scale)AP5070.2Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8Unverified
5Co-DETRmask AP57.1Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1Unverified
7ISDA (ResNet-50)APL55.7Unverified
8EVAmask AP55.5Unverified
9FD-SwinV2-Gmask AP55.4Unverified
10Mask Frozen-DETRmask AP55.3Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501Unverified
2Co-DETRmask AP56.6Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9Unverified
4InternImage-Hmask AP55.4Unverified
5EVAmask AP55Unverified
6Mask Frozen-DETRmask AP54.9Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2Unverified
9GLEE-Promask AP54.2Unverified
10SwinV2-G (HTC++)mask AP53.7Unverified