Human Parsing

32 papers with code • 0 benchmarks • 1 datasets

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) )

Datasets


Greatest papers with code

CCNet: Criss-Cross Attention for Semantic Segmentation

open-mmlab/mmsegmentation ICCV 2019

Compared with the non-local block, the proposed recurrent criss-cross attention module requires 11x less GPU memory usage.

Ranked #6 on Semantic Segmentation on FoodSeg103 (using extra training data)

Human Parsing Instance Segmentation +4

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

open-mmlab/mmpose 10 Apr 2018

Despite the noticeable progress in perceptual tasks like detection, instance segmentation and human parsing, computers still perform unsatisfactorily on visually understanding humans in crowded scenes, such as group behavior analysis, person re-identification and autonomous driving, etc.

Autonomous Driving Instance Segmentation +4

Self-Correction for Human Parsing

PeikeLi/Self-Correction-Human-Parsing 22 Oct 2019

To tackle the problem of learning with label noises, this work introduces a purification strategy, called Self-Correction for Human Parsing (SCHP), to progressively promote the reliability of the supervised labels as well as the learned models.

Human Parsing Human Part Segmentation +1

Multiple-Human Parsing in the Wild

ZhaoJ9014/Multi-Human-Parsing_MHP 19 May 2017

To address the multi-human parsing problem, we introduce a new multi-human parsing (MHP) dataset and a novel multi-human parsing model named MH-Parser.

Multi-Human Parsing

Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark

Engineering-Course/LIP_JPPNet 5 Apr 2018

To further explore and take advantage of the semantic correlation of these two tasks, we propose a novel joint human parsing and pose estimation network to explore efficient context modeling, which can simultaneously predict parsing and pose with extremely high quality.

Human Parsing Pose Estimation +1

Instance-level Human Parsing via Part Grouping Network

Engineering-Course/CIHP_PGN ECCV 2018

Instance-level human parsing towards real-world human analysis scenarios is still under-explored due to the absence of sufficient data resources and technical difficulty in parsing multiple instances in a single pass.

Edge Detection Human Parsing +2

Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer

MVIG-SJTU/WSHP CVPR 2018

In this paper, we present a novel method to generate synthetic human part segmentation data using easily-obtained human keypoint annotations.

Ranked #4 on Human Part Segmentation on PASCAL-Part (using extra training data)

Human Parsing Human Part Segmentation +2

Parsing R-CNN for Instance-Level Human Analysis

soeaver/Parsing-R-CNN CVPR 2019

Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance.

Human Part Segmentation Multi-Human Parsing +1

Parser-Free Virtual Try-on via Distilling Appearance Flows

geyuying/PF-AFN CVPR 2021

A recent pioneering work employed knowledge distillation to reduce the dependency of human parsing, where the try-on images produced by a parser-based method are used as supervisions to train a "student" network without relying on segmentation, making the student mimic the try-on ability of the parser-based model.

Human Parsing Knowledge Distillation +1