8 papers · 1 filter
Completing Partial Point Clouds with Outliers by Collaborative Completion and Segmentation
Changfeng Ma, Yang Yang, Jie Guo +2
Most existing point cloud completion methods are only applicable to partial point clouds without any noises and outliers, which does not always hold in practice. We propose in this…
CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language
Zhi Chen, Jingjing Li, Yadan Luo +2
Existing methods using generative adversarial approaches for Zero-Shot Learning (ZSL) aim to generate realistic visual features from class semantics by a single generative network,…
Alleviating Feature Confusion for Generative Zero-shot Learning
Jingjing Li, Mengmeng Jing, Ke Lu +3
Lately, generative adversarial networks (GANs) have been successfully applied to zero-shot learning (ZSL) and achieved state-of-the-art performance. By synthesizing virtual unseen…
Curiosity-driven Reinforcement Learning for Diverse Visual Paragraph Generation
Yadan Luo, Zi Huang, Zheng Zhang +3
Visual paragraph generation aims to automatically describe a given image from different perspectives and organize sentences in a coherent way. In this paper, we address three criti…
Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
Tan Wang, Xing Xu, Yang Yang +3
A major challenge in matching images and text is that they have intrinsically different data distributions and feature representations. Most existing approaches are based either on…
Coarse-to-Fine Annotation Enrichment for Semantic Segmentation Learning
Yadan Luo, Ziwei Wang, Zi Huang +2
Rich high-quality annotated data is critical for semantic segmentation learning, yet acquiring dense and pixel-wise ground-truth is both labor- and time-consuming. Coarse annotatio…