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 51100 of 462 papers

TitleStatusHype
@Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology0
Instruction-guided Multi-Granularity Segmentation and Captioning with Large Multimodal ModelCode1
COCO-OLAC: A Benchmark for Occluded Panoptic Segmentation and Image UnderstandingCode0
Panoptic-Depth Forecasting0
Resolving Inconsistent Semantics in Multi-Dataset Image Segmentation0
Dynamic Prompting of Frozen Text-to-Image Diffusion Models for Panoptic Narrative Grounding0
Towards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data0
A Simple and Generalist Approach for Panoptic Segmentation0
DQFormer: Towards Unified LiDAR Panoptic Segmentation with Decoupled Queries0
Image Segmentation in Foundation Model Era: A SurveyCode2
NuLite -- Lightweight and Fast Model for Nuclei Instance Segmentation and ClassificationCode1
LKCell: Efficient Cell Nuclei Instance Segmentation with Large Convolution KernelsCode1
SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation0
Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model0
MC-PanDA: Mask Confidence for Panoptic Domain AdaptationCode0
OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal ModelsCode1
A Fair Ranking and New Model for Panoptic Scene Graph GenerationCode1
From Easy to Hard: Learning Curricular Shape-aware Features for Robust Panoptic Scene Graph Generation0
Panoptic Segmentation of Galactic Structures in LSB Images0
Context-Aware Video Instance SegmentationCode2
Uni-DVPS: Unified Model for Depth-Aware Video Panoptic SegmentationCode1
Gradient-based Class Weighting for Unsupervised Domain Adaptation in Dense Prediction Visual Tasks0
PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction0
Task-aligned Part-aware Panoptic Segmentation through Joint Object-Part RepresentationsCode1
PanoSSC: Exploring Monocular Panoptic 3D Scene Reconstruction for Autonomous Driving0
1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation0
3rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation0
2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation0
A Good Foundation is Worth Many Labels: Label-Efficient Panoptic SegmentationCode1
4D Panoptic Scene Graph GenerationCode3
An Integrated Framework for Multi-Granular Explanation of Video SummarizationCode0
Building a Strong Pre-Training Baseline for Universal 3D Large-Scale PerceptionCode1
Panoptic Segmentation and Labelling of Lumbar Spine Vertebrae using Modified Attention Unet0
kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies0
The revenge of BiSeNet: Efficient Multi-Task Image Segmentation0
COCONut: Modernizing COCO Segmentation0
Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation0
JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments0
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt TuningCode2
Using Images as Covariates: Measuring Curb Appeal with Deep Learning0
PSALM: Pixelwise SegmentAtion with Large Multi-Modal ModelCode3
Better Call SAL: Towards Learning to Segment Anything in LidarCode2
PosSAM: Panoptic Open-vocabulary Segment AnythingCode2
Small, Versatile and Mighty: A Range-View Perception Framework0
PEM: Prototype-based Efficient MaskFormer for Image SegmentationCode2
Benchmarking the Robustness of Panoptic Segmentation for Automated Driving0
Generalizable Semantic Vision Query Generation for Zero-shot Panoptic and Semantic Segmentation0
Semantically-aware Neural Radiance Fields for Visual Scene Understanding: A Comprehensive ReviewCode1
Generalizable Entity Grounding via Assistance of Large Language Model0
UrbanGenAI: Reconstructing Urban Landscapes using Panoptic Segmentation and Diffusion Models0
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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