6 accepted papers
"Video summarization plays a vital role in improving video browsing efficiency and has various applications in action recognition and information retrieval. In order to generate summaries that can provide key information, existing works have been proposed to simultaneously explore the contribution o…
Lane detection methods based on anchors have received increasing attention, but fixed-shape anchors make it difficult to model complex lane line shapes. To solve this problem, we propose an Enhanced Curve Perception Network (ECPNet). Specifically, we propose a Layer-by-layer Context Fusion (LCF) mod…
Video summarization intends to automatically select meaningful segments from untrimmed videos. Although previous efforts have achieved remarkable progress, they still struggle to robustly aggregate and effectively process multi-granularity contextual information within videos, which hinders understa…
Learning fine-grained features is crucial to the performance improvement of person re-identification (Re-ID). Although existing methods have made significant progress, utilizing multi-level information to obtain fine-grained features has not been explored in this field. To alleviate this issue, we p…
Uncertainty in the estimation of the causal effect in observational studies is often due to unmeasured confounding, i.e., the presence of unobserved covariates linking treatments and outcomes. Instrumental Variables (IV) are commonly used to reduce the effects of unmeasured confounding. Existing met…
Matching methods are heavily used in the social and health sciences due to their interpretability. We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. The method proposed in this work aims to match units on a weighted H…