Who Blocks Who: Simultaneous clothing segmentation for grouping images

By Nan Wang, Haizhou Ai. 2011

78 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

Runway to Realway: Visual Analysis of Fashion (2015, methodology): “More closely related to the parsing approach used in this paper, there has been work on predicting semantic segmentations of clothing images [24, 25, 26], and we use the open source implementation from [26] as part of our pipeline.”
Semantic Object Parsing with Graph LSTM (2016, background): “Semantic Object Parsing: There has been increasing research interest on the semantic object parsing problem including the general object parsing [21][12][30][20][31], person part segmentation [9][8] and human parsing [23][4][32][33][34][35][36].”
Clothing Co-parsing by Joint Image Segmentation and Labeling (2014, background): “Later works studied on blocking models to segment clothes for highly occluded group images [28], or deformable spatial priors modeling for improving performance of clothing segmentation [8].”
Apparel Classification with Style (2012, background): “[27] also investigated segmentation of upper bodies, where the individuals occlude each other.”
Paper Doll Parsing: Retrieving Similar Styles to Parse Clothing Items (2013, background): “This is reflected in the growing interest in clothing related recognition papers [11, 10, 25, 16, 26, 7, 2, 4], perhaps boosted by recent advances in pose estimation [27, 3].”
Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos (2013, background): “However, many works focus on special clothing classes and applications [3] [15] [14] [5] [2] and it is only recently that generic clothing recognition has been directly tackled [16].”
Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set (2012, background): “Hasan et al. [12] and Wang et al. [17] proposed to use different priors to segment clothing.”
A High Performance CRF Model for Clothes Parsing (2014, background): “This is reflected in the growing interest in recognizing clothing from images [3,4,5,6,7,8,9,10], as this can enable a wide variety of applications such as trying on virtual garments in online shopping.”
Where to Buy It: Matching Street Clothing Photos in Online Shops (2015, background): “Some recent papers have demonstrated effective methods for clothing parsing, where the goal is to assign a semantic clothing label to each pixel in an image of a person [35, 38, 37, 7, 22].”
Semantic Object Parsing with Local-Global Long Short-Term Memory (2015, background): “Semantic Object Parsing: There have been increasing research works in the semantic object parsing problem including the general object parsing [31][33][24][4][11] and human parsing [37][36][6][32][25][21].”
Parsing Clothes in Unrestricted Images (2013, methodology): “Many methods [5, 8, 12, 14, 17] have been proposed to segment clothes in restrictive settings.”
Look into Person: Self-Supervised Structure-Sensitive Learning and a New Benchmark for Human Parsing (2017, unknown): “ the state-of-the-arts in terms of appearance variability and complexity, which includes 50,462 human images with pixel-wise annotations of 19 semantic parts. The recent progress on the human parsing [5,30,33, 32,9,28,26,20,18] has been achieved by improving the feature representations using convolu”