50 citations · 81 across the 5 of their papers we have counts for
5 papers
LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning
Huaiyu Li, Weiming Dong, Xing Mei +3
In this work, we propose a novel meta-learning approach for few-shot classification, which learns transferable prior knowledge across tasks and directly produces network parameters…
End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image
Seonghyeon Nam, Chongyang Ma, Menglei Chai +3
Time-lapse videos usually contain visually appealing content but are often difficult and costly to create. In this paper, we present an end-to-end solution to synthesize a time-lap…
SiCloPe: Silhouette-Based Clothed People
Ryota Natsume, Shunsuke Saito, Zeng Huang +4
We introduce a new silhouette-based representation for modeling clothed human bodies using deep generative models. Our method can reconstruct a complete and textured 3D model of a…
Deep Generative Modeling for Scene Synthesis via Hybrid Representations
Zaiwei Zhang, Zhenpei Yang, Chongyang Ma +4
We present a deep generative scene modeling technique for indoor environments. Our goal is to train a generative model using a feed-forward neural network that maps a prior distrib…
Image Retargetability
Fan Tang, Weiming Dong, Yiping Meng +4
Real-world applications could benefit from the ability to automatically retarget an image to different aspect ratios and resolutions, while preserving its visually and semantically…