1.2k citations · 1.2k across the 3 of their papers we have counts for
7 papers
ContraGAN: Contrastive Learning for Conditional Image Generation
Minguk Kang, Jaesik Park
Conditional image generation is the task of generating diverse images using class label information. Although many conditional Generative Adversarial Networks (GAN) have shown real…
High-dimensional Convolutional Networks for Geometric Pattern Recognition
Christopher Choy, Junha Lee, Rene Ranftl +2
Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces. We present high-dimensional convolutional networks (ConvNets)…
Future Video Synthesis with Object Motion Prediction
Yue Wu, Rongrong Gao, Jaesik Park +1
We present an approach to predict future video frames given a sequence of continuous video frames in the past. Instead of synthesizing images directly, our approach is designed to…
Combinatorial 3D Shape Generation via Sequential Assembly
Jungtaek Kim, Hyunsoo Chung, Jinhwi Lee +2
Sequential assembly with geometric primitives has drawn attention in robotics and 3D vision since it yields a practical blueprint to construct a target shape. However, due to its c…
HUMBI: A Large Multiview Dataset of Human Body Expressions
Zhixuan Yu, Jae Shin Yoon, In Kyu Lee +4
This paper presents a new large multiview dataset called HUMBI for human body expressions with natural clothing. The goal of HUMBI is to facilitate modeling view-specific appearanc…
Tangent Convolutions for Dense Prediction in 3D
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun +1
We present an approach to semantic scene analysis using deep convolutional networks. Our approach is based on tangent convolutions - a new construction for convolutional networks o…