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 76–100 of 199 papers

TitleStatusHype
GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing—0
FLOAT: Factorized Learning of Object Attributes for Improved Multi-object Multi-part Scene ParsingCode0
Boundary Corrected Multi-scale Fusion Network for Real-time Semantic Segmentation—0
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
MSP : Refine Boundary Segmentation via Multiscale Superpixel—0
TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing—0
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
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
Aerial-PASS: Panoramic Annular Scene Segmentation in Drone Videos—0
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
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
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
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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