Describing Clothing by Semantic Attributes

By Huizhong Chen, Andrew C. Gallagher, Bernd Girod. 2012

422 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

Citations in the corpus

Large scale visual recommendations from street fashion images (2014, methodology): “Other related papers on fashion domain [4, 9, 13, 14, 15] work on the problem of fashion parsing and similarity retrieval where the goal is to retrieve similar fashion image for a given query.”
Label-Embedding for Image Classification (2015, neutral): “Attributes have been used for image description [19], [18], [9], caption generation [27], [41], face recognition [29], [51], [10], image retrieval [28], [56], [15], action recognition [32], [69], novelty detection [62] and object classiﬁcation [30], [18], [64], [65], [34], [54], [38].”
DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images (2019, background): “With the development of fashion datasets [20, 5, 7, 3, 14, 12, 21, 1], significant progresses have been achieved in this area [2, 19, 17, 18, 9, 8].”
Hipster Wars: Discovering Elements of Fashion Styles (2014, background): “Additionally attributes have been explored specifically in the context of clothing for describing attributes of upper body clothing [1] or for jointly estimating clothing attributes in a CRF based approach [4].”
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].”
Clothing Co-parsing by Joint Image Segmentation and Labeling (2014, background): “In computer vision, several interesting works [30, 5, 17, 16] have been proposed on this task and showed promising results.”
Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose (2016, methodology): “Previous attribute approaches [2], [8], [9], [10], [28] use all defined parts (or poselets) for attribute classifications, and it means they assumed attributes are related to all body parts.”
Towards Unified Human Parsing and Pose Estimation (2014, background): “However, since the number of plausible human poses is exponentially large, the number of parameters that need to be estimated is prohibitive without a large dataset or a part sharing mechanism.”
Human Attribute Recognition by Rich Appearance Dictionary (2013, methodology): “The existing approaches [2, 5] have mainly focused on resolving the first issue - geometric variation of parts - by adopting pre-trained part detector or pose estimator.”
Understanding Blooming Human Groups in Social Networks (2015, background): “[11] described clothing appearance with semantic attributes by generating a list of nameable attributes for clothes on human body in unconstrained images.”
DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations (2016, methodology): “color, category, texture) [1, 3, 6], clothing locations (e.”
Fashion Landmark Detection in the Wild (2016, background): “Recent advances include predicting semantic attributes [16,8,9,17,3], clothes recognition and retrieval [4,18,19,20,2,3] and fashion trends discovery [6,21,7].”
Automatic Spatially-Aware Fashion Concept Discovery (2017, background): “Recently, researchers have annotated clothes with semantic attributes [9, 2, 8, 16, 11] (e.”
Deep Human Parsing with Active Template Regression (2015, background): “Despite the important role of human parsing in many fashion-related and human-centric applications [4], [21], it”
Style Finder: Fine-Grained Clothing Style Detection and Retrieval (2013, background): “Recent work focusing on computer vision methods applied to fashion and clothing [4] [6] [11] address the problem of clothing parsing and similarity retrieval, where the goal is to retrieve similar fashion imagery given a query.”
Where to Buy It: Matching Street Clothing Photos in Online Shops (2015, methodology): “Several methods have used attribute-based frameworks to describe, classify, or retrieve clothing [3, 4, 5].”
Webly Supervised Concept Expansion for General Purpose Vision Models (2022, methodology): “We source adjectives from several datasets that have a large number of adjectives [10, 19, 40, 41, 43, 59, 60, 68, 79].”
A Unified Probabilistic Approach Modeling Relationships between Attributes and Objects (2013, background): “Recently, Chen et al. [2] apply a CRF model to improve attribute predictions for the clothing appearance describing tasks.”