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 31–40 of 199 papers

TitleStatusHype
Minimal Solvers for Single-View Lens-Distorted Camera Auto-CalibrationCode1
Malleable 2.5D Convolution: Learning Receptive Fields along the Depth-axis for RGB-D Scene ParsingCode1
Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph GenerationCode1
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual RecognitionCode1
CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local RefinementCode1
Strip Pooling: Rethinking Spatial Pooling for Scene ParsingCode1
EPSNet: Efficient Panoptic Segmentation Network with Cross-layer Attention FusionCode1
Semantic Flow for Fast and Accurate Scene ParsingCode1
GFF: Gated Fully Fusion for Semantic SegmentationCode1
Context-Aware Synthesis and Placement of Object InstancesCode1
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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