Multi-Human Parsing
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Benchmarks
Most implemented
Mask R-CNN
Semantic Instance Segmentation with a Discriminative Loss Function
Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
Parsing R-CNN for Instance-Level Human Analysis
Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
Multiple-Human Parsing in the Wild
Papers
Leveraging Multi-View Weak Supervision for Occlusion-Aware Multi-Human Parsing
Multi-human parsing is the task of segmenting human body parts while associating each part to the person it belongs to, combining instance-level and part-level information for fine-grained human understanding. In this wo…
Human Instance SegmentationMulti-Human ParsingUniParser: Multi-Human Parsing with Unified Correlation Representation Learning
Multi-human parsing is an image segmentation task necessitating both instance-level and fine-grained category-level information. However, prior research has typically processed these two types of information through sepa…
Human ParsingImage SegmentationMulti-Human ParsingRepresentation Learning+1Single-stage Multi-human Parsing via Point Sets and Center-based Offsets
This work studies the multi-human parsing problem. Existing methods, either following top-down or bottom-up two-stage paradigms, usually involve expensive computational costs. We instead present a high-performance Single…
Human ParsingMulti-Human ParsingNondiscriminatory Treatment: a straightforward framework for multi-human parsing
Multi-human parsing aims to segment every body part of every human instance. Nearly all state-of-the-art methods follow the "detection first" or "segmentation first" pipelines. Different from them, we present an end-to-e…
Human ParsingInstance SegmentationMulti-Human ParsingSegmentation+1Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
Supervised deep learning with pixel-wise training labels has great successes on multi-person part segmentation. However, data labeling at pixel-level is very expensive. To solve the problem, people have been exploring to…
Domain AdaptationHuman Part SegmentationMulti-Human ParsingPose Estimation+1Parsing R-CNN for Instance-Level Human Analysis
Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different…
Human ParsingHuman Part SegmentationMulti-Human ParsingPose Estimation