SOTAVerified

Human Parsing

Human parsing is the task of segmenting a human image into different fine-grained semantic parts such as head, torso, arms and legs.

( Image credit: Multi-Human-Parsing (MHP) )

Papers

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Showing 101–110 of 125 papers

TitleStatusHype
Affinity-aware Compression and Expansion Network for Human Parsing—0
RepParser: End-to-End Multiple Human Parsing with Representative Parts—0
RobustFusion: Robust Volumetric Performance Reconstruction under Human-object Interactions from Monocular RGBD Stream—0
Robust Person Re-Identification through Contextual Mutual Boosting—0
Scanpaths in reading are informative about sentence processing—0
SCHNet: SAM Marries CLIP for Human Parsing—0
Texture-Based Input Feature Selection for Action Recognition—0
Self-Learning with Rectification Strategy for Human Parsing—0
AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing—0
From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding—0
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All datasets4D-DRESSPASCAL Context

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Graphonomy_InnermAcc0.97—Unverified
2CDGNet_InnermAcc0.92—Unverified
3Graphonomy_OutermAcc0.92—Unverified
4SCHP_InnermAcc0.91—Unverified
5CDGNet_OutermAcc0.89—Unverified
6SCHP_OutermAcc0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1InvPTmIoU67.61—Unverified