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
Texture-Based Input Feature Selection for Action Recognition—0
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation—0
Macro-Micro Adversarial Network for Human ParsingCode0
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human ParsingCode0
Multiple-Human Parsing in the WildCode0
Single-stage Multi-human Parsing via Point Sets and Center-based OffsetsCode0
Look into Person: Joint Body Parsing & Pose Estimation Network and A New BenchmarkCode0
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge TransferCode0
Instance-level Human Parsing via Part Grouping NetworkCode0
C-DLinkNet: considering multi-level semantic features for human parsingCode0
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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