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
Keypoint Based Weakly Supervised Human Parsing—0
Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation—0
Adaptive Temporal Encoding Network for Video Instance-level Human ParsingCode0
Instance-level Human Parsing via Part Grouping NetworkCode0
Macro-Micro Adversarial Network for Human ParsingCode0
Eliminating Background-Bias for Robust Person Re-Identification—0
Human Pose Estimation With Parsing Induced Learner—0
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge TransferCode0
Progressive refinement: a method of coarse-to-fine image parsing using stacked network—0
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-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