Papers Human Part Segmentation
“Human Part Segmentation” 태그가 달린 논문 20편 · 필터 해제
OpenHuman4D: Open-Vocabulary 4D Human Parsing
Understanding dynamic 3D human representation has become increasingly critical in virtual and extended reality applications. However, existing human part segmentation methods are constrained by reliance on closed-set dat…
Human Part SegmentationVideo Object TrackingHuman ParsingSapiens: Foundation for Human Vision Models
We present Sapiens, a family of models for four fundamental human-centric vision tasks -- 2D pose estimation, body-part segmentation, depth estimation, and surface normal prediction. Our models natively support 1K high-r…
2D Human Pose Estimation2D Pose EstimationDepth EstimationHuman Part Segmentation+3Hulk: A Universal Knowledge Translator for Human-Centric Tasks
Human-centric perception tasks, e.g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports analysis. There is a recent surge to dev…
3D Human Pose EstimationAction RecognitionHuman Mesh RecoveryHuman Part Segmentation+7UniHCP: A Unified Model for Human-Centric Perceptions
Human-centric perceptions (e.g., pose estimation, human parsing, pedestrian detection, person re-identification, etc.) play a key role in industrial applications of visual models. While specific human-centric tasks have …
2D Pose EstimationAttributeHuman ParsingHuman Part Segmentation+7Parsing Objects at a Finer Granularity: A Survey
Fine-grained visual parsing, including fine-grained part segmentation and fine-grained object recognition, has attracted considerable critical attention due to its importance in many real-world applications, e.g., agricu…
Fine-Grained Visual RecognitionHuman Part SegmentationObject RecognitionSegmentation+1KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondences
Human densepose estimation, aiming at establishing dense correspondences between 2D pixels of human body and 3D human body template, is a key technique in enabling machines to have an understanding of people in images. I…
Human Part SegmentationTransfer LearningMotion-Aware Transformer For Occluded Person Re-identification
Recently, occluded person re-identification(Re-ID) remains a challenging task that people are frequently obscured by other people or obstacles, especially in a crowd massing situation. In this paper, we propose a self-su…
DecoderHuman Part SegmentationKeypoint DetectionOccluded Person Re-Identification+2PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation
Image Segmentation plays an essential role in computer vision and image processing with various applications from medical diagnosis to autonomous car driving. A lot of segmentation algorithms have been proposed for addre…
Autonomous DrivingHuman Part SegmentationImage SegmentationMedical Diagnosis+3Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding
In this technical report, we present two novel datasets for image scene understanding. Both datasets have annotations compatible with panoptic segmentation and additionally they have part-level labels for selected semant…
Human Part SegmentationPanoptic SegmentationPart-aware Panoptic SegmentationScene Understanding+2Self-Correction for Human Parsing
Labeling pixel-level masks for fine-grained semantic segmentation tasks, e.g. human parsing, remains a challenging task. The ambiguous boundary between different semantic parts and those categories with similar appearanc…
Human ParsingHuman Part SegmentationSemantic SegmentationCross-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 EstimationInstance-level Human Parsing via Part Grouping Network
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. Se…
Edge DetectionHuman ParsingHuman Part SegmentationRepresentation LearningMacro-Micro Adversarial Network for Human Parsing
In human parsing, the pixel-wise classification loss has drawbacks in its low-level local inconsistency and high-level semantic inconsistency. The introduction of the adversarial network tackles the two problems using a …
Human ParsingHuman Part SegmentationSemantic SegmentationWeakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
Human body part parsing, or human semantic part segmentation, is fundamental to many computer vision tasks. In conventional semantic segmentation methods, the ground truth segmentations are provided, and fully convolutio…
Human ParsingHuman Part SegmentationSegmentationSemantic Segmentation+1Dense and Low-Rank Gaussian CRFs Using Deep Embeddings
In this work we introduce a structured prediction model that endows the Deep Gaussian Conditional Random Field (G-CRF) with a densely connected graph structure. We keep memory and computational complexity under control b…
GPUHuman Part SegmentationSaliency PredictionSegmentation+2Ubernet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited Memory
In this work we train in an end-to-end manner a convolutional neural network (CNN) that jointly handles low-, mid-, and high-level vision tasks in a unified architecture. Such a network can act like a `swiss knife' fo…
Boundary DetectionGPUHuman Part Segmentationobject-detection+5Mask R-CNN
We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask fo…
3D Instance SegmentationHuman Part SegmentationInstance SegmentationKeypoint Detection+14Learning from Synthetic Humans
Estimating human pose, shape, and motion from images and videos are fundamental challenges with many applications. Recent advances in 2D human pose estimation use large amounts of manually-labeled training data for learn…
2D Human Pose Estimation3D Human Pose EstimationHuman Part SegmentationPose Estimation+1UberNet: Training a `Universal' Convolutional Neural Network for Low-, Mid-, and High-Level Vision using Diverse Datasets and Limited Memory
In this work we introduce a convolutional neural network (CNN) that jointly handles low-, mid-, and high-level vision tasks in a unified architecture that is trained end-to-end. Such a universal network can act like a `s…
Boundary DetectionGPUHuman Part Segmentationobject-detection+4