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 121–130 of 199 papers

TitleStatusHype
Weakly Supervised Scene Parsing with Point-based Distance Metric Learning—0
What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing—0
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 Segmentation—0
Window Detection In Facade Imagery: A Deep Learning Approach Using Mask R-CNN—0
3D Scene Parsing via Class-Wise Adaptation—0
A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects—0
Active Scene Understanding via Online Semantic Reconstruction—0
Adaptive Context Network for Scene Parsing—0
Adaptive Exponential Smoothing for Online Filtering of Pixel Prediction Maps—0
A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing—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