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 91–100 of 125 papers

TitleStatusHype
Semantic-Human: Neural Rendering of Humans from Monocular Video with Human Parsing—0
Spatial Cascaded Clustering and Weighted Memory for Unsupervised Person Re-identification—0
The Active-Filler Strategy in a Move-Eager Left-Corner Minimalist Grammar Parser—0
Towards Multi-pose Guided Virtual Try-on Network—0
Towards Rich Feature Discovery With Class Activation Maps Augmentation for Person Re-Identification—0
Towards Unified Human Parsing and Pose Estimation—0
TruePose: Human-Parsing-guided Attention Diffusion for Full-ID Preserving Pose Transfer—0
Texture-Based Input Feature Selection for Action Recognition—0
DROP: Decouple Re-Identification and Human Parsing with Task-specific Features for Occluded Person Re-identificationCode0
Devil in the Details: Towards Accurate Single and Multiple 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