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 101–125 of 199 papers

TitleStatusHype
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models—0
Semantic Segmentation on VSPW Dataset through Contrastive Loss and Multi-dataset Training Approach—0
Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024—0
Single-View 3D Scene Parsing by Attributed Grammar—0
Soft Correspondences in Multimodal Scene Parsing—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—0
Spatially Constrained Location Prior for Scene Parsing—0
SPGNet: Semantic Prediction Guidance for Scene Parsing—0
TBN-ViT: Temporal Bilateral Network with Vision Transformer for Video Scene Parsing—0
Hardware implementation of timely reliable Bayesian decision-making using memristors—0
Treasure What You Have: Exploiting Similarity in Deep Neural Networks for Efficient Video Processing—0
Variational Context-Deformable ConvNets for Indoor Scene Parsing—0
Video Scene Parsing with Predictive Feature Learning—0
Visual Traffic Knowledge Graph Generation from Scene Images—0
VSPW: A Large-scale Dataset for Video Scene Parsing in the Wild—0
Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving—0
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
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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