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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 199 papers

TitleStatusHype
Cross-CBAM: A Lightweight network for Scene Segmentation—0
Treasure What You Have: Exploiting Similarity in Deep Neural Networks for Efficient Video Processing—0
RT-K-Net: Revisiting K-Net for Real-Time Panoptic SegmentationCode1
Local and Global Contextual Features Fusion for Pedestrian Intention Prediction—0
DPF: Learning Dense Prediction Fields with Weak SupervisionCode1
Traffic Scene Parsing through the TSP6K DatasetCode1
Visual Traffic Knowledge Graph Generation from Scene Images—0
Re:PolyWorld - A Graph Neural Network for Polygonal Scene Parsing—0
Uni-3D: A Universal Model for Panoptic 3D Scene ReconstructionCode1
Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving—0
Show:102550
← PrevPage 4 of 20Next →
All datasetsPGDP5KCityscapes test

Benchmark Results

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