6 accepted papers
Video object detection is a fundamental yet challenging task in computer vision. Recently, DETR-based methods have gained prominence in this domain owing to their powerful global modeling capabilities. However, these methods are still confronted with two key limitations: frame-agnostic initializatio
Recently, memory-based methods have achieved progress in semi-supervised video object segmentation. However, these methods still suffer from unstructured challenges, such as object transformations, occlusions and disappearance-reappearance. To this end, we propose a Holistic Correction Network (HCNe…
Faithful opinion summarization task refers to generating a summary for a set of documents that covers the majority and minority opinions in documents. Inspired by the cognitive science that argument facet is the focus of an opinion, we propose the facets-guided opinion summarization method (FacSum).
Two-view correspondence learning is a key task in computer vision, which aims to establish reliable matching relationships for applications such as camera pose estimation and 3D reconstruction. However, existing methods have limitations in local geometric modeling and cross-stage information optimiz
In recent years, Correlation Filter (CF) based tracking methods using Convolutional Neural Network (CNN) features have achieved the state-of-the-art performance for object tracking. However, how to design an efficient deep CF based tracking method has not been well studied in the literature. To addr…
Visual tracking aims at both robust target classification and accurate localization. However, the reliability of the target bounding box and classification score are not properly addressed by most existing trackers, resulting in inaccurate tracking performance. In this paper, we propose to learn bou…