SOTAVerified

Scene Parsing

Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description

Papers

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Showing 51–100 of 199 papers

TitleStatusHype
Aerial Scene Parsing: From Tile-level Scene Classification to Pixel-wise Semantic Labeling—0
Fully Decoupled Residual ConvNet for Real-Time Railway Scene Parsing of UAV Aerial Images—0
ESCNet: Gaze Target Detection With the Understanding of 3D Scenes—0
Edge-aware Guidance Fusion Network for RGB Thermal Scene ParsingCode1
Mesh Convolution with Continuous Filters for 3D Surface ParsingCode1
MSP : Refine Boundary Segmentation via Multiscale Superpixel—0
TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing—0
Pointly-supervised 3D Scene Parsing with Viewpoint BottleneckCode1
Exploiting Spatial-Temporal Semantic Consistency for Video Scene Parsing—0
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models—0
Memory Based Video Scene Parsing—0
BORM: Bayesian Object Relation Model for Indoor Scene RecognitionCode1
Global Aggregation then Local Distribution for Scene ParsingCode1
Resource Efficient Mountainous Skyline Extraction using Shallow LearningCode1
Window Detection In Facade Imagery: A Deep Learning Approach Using Mask R-CNN—0
VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild—0
Part-aware Panoptic SegmentationCode1
Fast and Accurate Scene Parsing via Bi-direction Alignment NetworksCode1
Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos—0
Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic ReasoningCode1
Editable Free-viewpoint Video Using a Layered Neural RepresentationCode1
3D-to-2D Distillation for Indoor Scene ParsingCode1
Evidential fully convolutional network for semantic segmentationCode1
AttaNet: Attention-Augmented Network for Fast and Accurate Scene ParsingCode1
Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—0
Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene GraphsCode2
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road ScenesCode1
ORDNet: Capturing Omni-Range Dependencies for Scene Parsing—0
An Evolution of CNN Object Classifiers on Low-Resolution Images—0
Interaction via Bi-Directional Graph of Semantic Region Affinity for Scene Parsing—0
Class Attention Network for Semantic Segmentation of Remote Sensing Images—0
Minimal Solvers for Single-View Lens-Distorted Camera Auto-CalibrationCode1
Multi-layer Feature Aggregation for Deep Scene Parsing Models—0
A Dilated Residual Hierarchically Fashioned Segmentation Framework for Extracting Gleason Tissues and Grading Prostate Cancer from Whole Slide ImagesCode0
LID 2020: The Learning from Imperfect Data Challenge Results—0
Automatic Quantification of Settlement Damage using Deep Learning of Satellite Images—0
GINet: Graph Interaction Network for Scene ParsingCode0
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene ParsingCode1
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph GenerationCode1
Non-parametric spatially constrained local prior for scene parsing on real-world data—0
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual RecognitionCode1
Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions—0
Variational Context-Deformable ConvNets for Indoor Scene Parsing—0
CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local RefinementCode1
Strip Pooling: Rethinking Spatial Pooling for Scene ParsingCode1
EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention FusionCode1
Night-time Scene Parsing with a Large Real Dataset—0
Semantic Flow for Fast and Accurate Scene ParsingCode1
Real-Time Panoptic Segmentation from Dense Detections—0
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All datasetsPGDP5KCityscapes test

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PGDPNetTotal Accuracy84.7—Unverified
2Inter-GPSTotal Accuracy27.3—Unverified
#ModelMetricClaimedVerifiedStatus
1VCD No CoarsemIoU82.3—Unverified