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 141–150 of 199 papers

TitleStatusHype
Class Attention Network for Semantic Segmentation of Remote Sensing Images—0
Compositional Factorization of Visual Scenes with Convolutional Sparse Coding and Resonator Networks—0
Consensus Feature Network for Scene Parsing—0
Context Driven Scene Parsing with Attention to Rare Classes—0
Context-Integrated and Feature-Refined Network for Lightweight Object Parsing—0
Cross-CBAM: A Lightweight network for Scene Segmentation—0
Cutting Edge: Soft Correspondences in Multimodal Scene Parsing—0
Deep and Wide Multiscale Recursive Networks for Robust Image Labeling—0
Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation—0
Deep Deconvolutional Networks for 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