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 14511475 of 2262 papers

TitleStatusHype
A Benchmark of Long-tailed Instance Segmentation with Noisy LabelsCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning?0
Rethinking Implicit Neural Representations for Vision Learners0
Task-Specific Data Augmentation and Inference Processing for VIPriors Instance Segmentation Challenge0
The Runner-up Solution for YouTube-VIS Long Video Challenge 20220
SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification0
3D-QueryIS: A Query-based Framework for 3D Instance Segmentation0
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation0
Label-Efficient Object Detection via Region Proposal Network Pre-Training0
Robust Online Video Instance Segmentation with Track QueriesCode0
PAI3D: Painting Adaptive Instance-Prior for 3D Object Detection0
Forecasting Future Instance Segmentation with Learned Optical Flow and Warping0
Deep Instance Segmentation and Visual Servoing to Play Jenga with a Cost-Effective Robotic System0
Recursive Cross-View: Use Only 2D Detectors to Achieve 3D Object Detection without 3D Annotations0
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
MR-NOM: Multi-scale Resolution of Neuronal cells in Nissl-stained histological slices via deliberate Over-segmentation and Merging0
Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding0
BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield imagesCode0
Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks0
Could Giant Pretrained Image Models Extract Universal Representations?0
Deep Learning based Defect classification and detection in SEM images: A Mask R-CNN approach0
CircleSnake: Instance Segmentation with Circle RepresentationCode0
Two-Level Temporal Relation Model for Online Video Instance SegmentationCode0
Grafting Vision Transformers0
Show:102550
← PrevPage 59 of 91Next →

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
8GLEE-Promask AP54.2Unverified
9ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2Unverified
10SwinV2-G (HTC++)mask AP53.7Unverified