SOTAVerified

Panoptic Segmentation

Panoptic Segmentation is a computer vision task that combines semantic segmentation and instance segmentation to provide a comprehensive understanding of the scene. The goal of panoptic segmentation is to segment the image into semantically meaningful parts or regions, while also detecting and distinguishing individual instances of objects within those regions. In a given image, every pixel is assigned a semantic label, and pixels belonging to "things" classes (countable objects with instances, like cars and people) are assigned unique instance IDs. ( Image credit: Detectron2 )

Papers

Showing 251300 of 462 papers

TitleStatusHype
CASNet: Common Attribute Support Network for image instance and panoptic segmentation0
CFNet: Learning Correlation Functions for One-Stage Panoptic Segmentation0
ClaraVid: A Holistic Scene Reconstruction Benchmark From Aerial Perspective With Delentropy-Based Complexity Profiling0
COCONut: Modernizing COCO Segmentation0
COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation0
CoMFormer: Continual Learning in Semantic and Panoptic Segmentation0
Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation0
Connectivity-constrained interactive annotations for panoptic segmentation0
Connectivity-constrained Interactive Panoptic Segmentation0
Contextual Associated Triplet Queries for Panoptic Scene Graph Generation0
Contextual Image Parsing via Panoptic Segment Sorting0
Learning Segmented 3D Gaussians via Efficient Feature Unprojection for Zero-shot Neural Scene Segmentation0
CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Clouds0
DeeperLab: Single-Shot Image Parser0
Deep Learning Based Dominant Index Lesion Segmentation for MR-guided Radiation Therapy of Prostate Cancer0
Detecting Reflections by Combining Semantic and Instance Segmentation0
Digital Histopathology with Graph Neural Networks: Concepts and Explanations for Clinicians0
DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation0
DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries0
DreamMask: Boosting Open-vocabulary Panoptic Segmentation with Synthetic Data0
Dual Complementary Dynamic Convolution for Image Recognition0
Dynamic Prompting of Frozen Text-to-Image Diffusion Models for Panoptic Narrative Grounding0
EfficientLPS: Efficient LiDAR Panoptic Segmentation0
EfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation0
Ensembling Instance and Semantic Segmentation for Panoptic Segmentation0
Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey0
Exploiting weakly supervised visual patterns to learn from partial annotations0
Seeing Eye to AI: Comparing Human Gaze and Model Attention in Video Memorability0
Fast Object Classification and Meaningful Data Representation of Segmented Lidar Instances0
Fast Panoptic Segmentation Network0
Feature Pyramid Encoding Network for Real-time Semantic Segmentation0
FreeSeg: Unified, Universal and Open-Vocabulary Image Segmentation0
From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation0
Generalizable Entity Grounding via Assistance of Large Language Model0
Generalizable Semantic Vision Query Generation for Zero-shot Panoptic and Semantic Segmentation0
GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Network0
Gradient-based Class Weighting for Unsupervised Domain Adaptation in Dense Prediction Visual Tasks0
Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation0
Hierarchical Lovasz Embeddings for Proposal-Free Panoptic Segmentation0
UniDAformer: Unified Domain Adaptive Panoptic Segmentation Transformer via Hierarchical Mask Calibration0
HieraSurg: Hierarchy-Aware Diffusion Model for Surgical Video Generation0
Hybrid Tracker with Pixel and Instance for Video Panoptic Segmentation0
Improving Panoptic Segmentation at All Scales0
Improving vision-language alignment with graph spiking hybrid Networks0
Indoor Navigation Assistance for Visually Impaired People via Dynamic SLAM and Panoptic Segmentation with an RGB-D Sensor0
In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding0
Instance and Panoptic Segmentation Using Conditional Convolutions0
Dense Semantic Forecasting in Video by Joint Regression of Features and Feature Motion0
JPPF: Multi-task Fusion for Consistent Panoptic-Part Segmentation0
JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Mask DINO (single scale)PQ59.5Unverified
2kMaX-DeepLab (single-scale)PQ58.5Unverified
3Mask2Former (Swin-L)PQ58.3Unverified
4Panoptic SegFormer (Swin-L)PQ56.2Unverified
5Panoptic SegFormer (PVTv2-B5)PQ55.8Unverified
6CMT-DeepLab (single-scale)PQ55.7Unverified
7K-Net (Swin-L)PQ55.2Unverified
8MaskConver (ResNet50, single-scale)PQ53.6Unverified
9MaskFormer (Swin-L)PQ53.3Unverified
10Panoptic FCN* (Swin-L)PQ52.7Unverified
#ModelMetricClaimedVerifiedStatus
1HyperSeg (Swin-B)PQ61.2Unverified
2OneFormer (InternImage-H,single-scale)PQ60Unverified
3UMG-CLIP-E/14PQ59.5Unverified
4OpenSeeD (SwinL, single-scale)PQ59.5Unverified
5MasK DINO (SwinL,single-scale)PQ59.4Unverified
6EoMT (DINOv2-g, single-scale, 1280x1280)PQ59.2Unverified
7UMG-CLIP-L/14PQ58.9Unverified
8Panoptic FCN* (Swin-L, single-scale)PQth58.5Unverified
9DiNAT-L (single-scale, Mask2Former)PQ58.5Unverified
10ViT-Adapter-L (single-scale, BEiTv2 pretrain, Mask2Former)PQ58.4Unverified
#ModelMetricClaimedVerifiedStatus
1OneFormer (DiNAT-L, single-scale)PQ46.7Unverified
2OneFormer (ConvNeXt-L, single-scale)PQ46.4Unverified
3Panoptic FCN* (Swin-L, single-scale)PQ45.7Unverified
4Panoptic-DeepLab (SWideRNet-(1, 1, 4.5), multi-scale)PQ44.8Unverified
5Panoptic FCN* (ResNet-50-FPN)PQst42.3Unverified
6Mask2Former + Intra-Batch Supervision (ResNet-50)PQ42.2Unverified
7Axial-DeepLab-L (multi-scale)PQ41.1Unverified
8EfficientPSPQ40.6Unverified
9Panoptic-DeepLab (X71)PQ40.5Unverified
10AdaptIS (ResNeXt-101)PQ40.3Unverified
#ModelMetricClaimedVerifiedStatus
1OneFormer (ConvNeXt-L, single-scale, Mapillary Vistas-Pretrained)PQ68Unverified
2Panoptic-DeepLab (SWideRNet [1, 1, 4.5], Mapillary, multi-scale)PQ67.8Unverified
3EfficientPSPQ67.1Unverified
4Axial-DeepLab-XL (Mapillary Vistas, multi-scale)PQ66.6Unverified
5kMaX-DeepLab (single-scale)PQ66.2Unverified
6Panoptic-DeeplabPQ65.5Unverified
7EfficientPS (Cityscapes-fine)PQ62.9Unverified
8COPS (ResNet-50)PQ60Unverified
9SOGNet (ResNet-50)PQ60Unverified
10Dynamically Instantiated NetworkPQ55.4Unverified
#ModelMetricClaimedVerifiedStatus
1Mask2Former (Swin-B)PQ41.7Unverified
2Panoptic FPN (ResNet-50)PQ40.1Unverified
3Mask2Former (Swin-T)PQ39.2Unverified
4Panoptic FPN (ResNet-101)PQ38.7Unverified
5Mask2Former (ResNet-50)PQ37.6Unverified
6Mask2Former (ResNet-101)PQ37.2Unverified
7Panoptic Deeplab (ResNet-50)PQ34.7Unverified
8MaX-DeepLabPQ31.9Unverified
#ModelMetricClaimedVerifiedStatus
1SuperClusterPQ50.1Unverified
2PointGroup (Xiang 2023)PQ42.3Unverified
3KPConv (Xiang 2023)PQ41.8Unverified
4MinkowskiNet (Xiang 2023)PQ39.2Unverified
5PointNet++ (Xiang 2023)PQ24.6Unverified
#ModelMetricClaimedVerifiedStatus
1OneFormer3DPQ71.2Unverified
2PanopticNDT (10cm)PQ59.19Unverified
3SuperClusterPQ58.7Unverified
4PanopticFusion (with CRF)PQ33.5Unverified
5SceneGraphFusion (NN mapping)PQ31.5Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientPSPQ51.1Unverified
2SeamlessPQ48.5Unverified
3UPSNetPQ47.1Unverified
4Panoptic FPNPQ46.7Unverified
#ModelMetricClaimedVerifiedStatus
1EfficientPSPQ43.7Unverified
2SeamlessPQ42.2Unverified
3UPSNetPQ39.9Unverified
4Panoptic FPNPQ39.3Unverified
#ModelMetricClaimedVerifiedStatus
1LKCellPQ50.8Unverified
2CellViT-SAM-HPQ50.62Unverified
3TSFDPQ50.4Unverified
4NuLite-HPQ49.81Unverified
#ModelMetricClaimedVerifiedStatus
1OneFormer3DPQ71.2Unverified
2SuperClusterPQ58.7Unverified
3PanopticFusionPQ33.5Unverified
4SceneGraphFusionPQ31.5Unverified
#ModelMetricClaimedVerifiedStatus
1Exchanger+Mask2FormerPQ52.6Unverified
2Exchanger+Unet+PaPsPQ47.8Unverified
3U-TAE + PaPsPQ40.4Unverified
#ModelMetricClaimedVerifiedStatus
1VAN-B6*PQ58.2Unverified
2PFPN (ideal number of groups)PQ42.15Unverified
#ModelMetricClaimedVerifiedStatus
1CAFuser (Swin-T)PQ59.7Unverified
2MUSES (Mask2Former /w 4xSwin-T)PQ53.6Unverified
#ModelMetricClaimedVerifiedStatus
1EMSANet (2x ResNet-34 NBt1D, PanopticNDT version, finetuned)PQ51.15Unverified
2EMSANetPQ47.38Unverified
#ModelMetricClaimedVerifiedStatus
1P3FormerPQ0.65Unverified
2DS-NetPQ0.56Unverified
#ModelMetricClaimedVerifiedStatus
1MasQCLIPPQ23.3Unverified