Development of a Conceptual Model to Explore Consumers\u27 Motivations To Collaboratively Consume Fashion

The phenomenon of collaborative consumption (CC) or sharing economy , where people coordinate acquisition and distribution of a resource for a fee or other compensation has gained tremendous popularity in recent years. The popularity of CC practice has also been observed in the fashion retail industry through two distinct forms: online fashion rental services and peer-to-peer (P2P) platforms that allow for selling and exchanging of goods. The purpose of this conceptual paper is to develop a conceptual framework for studying various motivations of consumers who collaboratively consume fashion. Drawing on extant literature, a conceptual framework incorporating utilitarian and hedonic motives, sustainability motive, and the moderating role of perceived risk on the attitude toward CC is proposed

QCD sum rules with two-point correlation function

We construct three different sum rules from the two-point correlation function with pion, $i\int d^4x e^{iq\cdot x} <0| T J_N(x) {\bar J}_N(0)|\pi(p)>$, beyond the soft-pion limit. The PS and PV coupling schemes in the construction of the phenomenological side are carefully considered in each sum rule. We discuss the dependence of the result on the specific Dirac structure and identify the source of the dependence by making specific models for higher resonances.Comment: 4 pages, LaTex, Talk presented at the KEK-Tanashi International Symposium on ``Physics of Hadrons and Nuclei'', Dec. 14-17, 1998 Tokyo, Japan, Submitted to Nuclear Physics

Recursive Video Lane Detection

A novel algorithm to detect road lanes in videos, called recursive video lane detector (RVLD), is proposed in this paper, which propagates the state of a current frame recursively to the next frame. RVLD consists of an intra-frame lane detector (ILD) and a predictive lane detector (PLD). First, we design ILD to localize lanes in a still frame. Second, we develop PLD to exploit the information of the previous frame for lane detection in a current frame. To this end, we estimate a motion field and warp the previous output to the current frame. Using the warped information, we refine the feature map of the current frame to detect lanes more reliably. Experimental results show that RVLD outperforms existing detectors on video lane datasets. Our codes are available at https://github.com/dongkwonjin/RVLD.Comment: ICCV 2023 accepte