output
20152023
most citedClothing Co-Parsing by Joint Image Segmentation and Labeling

154 citations

11 papers

cs.CV20234 cited

Evaluating the Efficacy of Skincare Product: A Realistic Short-Term Facial Pore Simulation

Ling Li, Bandara Dissanayake, Tatsuya Omotezako +8

Simulating the effects of skincare products on face is a potential new way to communicate the efficacy of skincare products in skin diagnostics and product recommendations. Further…

cs.AI2017

From Preference-Based to Multiobjective Sequential Decision-Making

Paul Weng

In this paper, we present a link between preference-based and multiobjective sequential decision-making. While transforming a multiobjective problem to a preference-based one is qu…

cs.AI20173 cited

Finding Risk-Averse Shortest Path with Time-dependent Stochastic Costs

Dajian Li, Paul Weng, Orkun Karabasoglu

In this paper, we tackle the problem of risk-averse route planning in a transportation network with time-dependent and stochastic costs. To solve this problem, we propose an adapta…

cs.CV201537 cited

Deep Joint Task Learning for Generic Object Extraction

Xiaolong Wang, Liliang Zhang, Liang Lin +2

This paper investigates how to extract objects-of-interest without relying on hand-craft features and sliding windows approaches, that aims to jointly solve two sub-tasks: (i) rapi…

cs.CV2015154 cited

Clothing Co-Parsing by Joint Image Segmentation and Labeling

Wei Yang, Ping Luo, Liang Lin

This paper aims at developing an integrated system of clothing co-parsing, in order to jointly parse a set of clothing images (unsegmented but annotated with tags) into semantic co…

cs.CV20154 cited

Deep Boosting: Layered Feature Mining for General Image Classification

Zhanglin Peng, Liang Lin, Ruimao Zhang +1

Constructing effective representations is a critical but challenging problem in multimedia understanding. The traditional handcraft features often rely on domain knowledge, limitin…