activity
20192021
most citedSpatial Semantic Embedding Network: Fast 3D Instance Segmentation with Deep Metric Learning

13 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20215 cited

SGoLAM: Simultaneous Goal Localization and Mapping for Multi-Object Goal Navigation

Junho Kim, Eun Sun Lee, Mingi Lee +2

We present SGoLAM, short for simultaneous goal localization and mapping, which is a simple and efficient algorithm for Multi-Object Goal navigation. Given an agent equipped with an…

cs.CV2021

GATSBI: Generative Agent-centric Spatio-temporal Object Interaction

Cheol-Hui Min, Jinseok Bae, Junho Lee +1

We present GATSBI, a generative model that can transform a sequence of raw observations into a structured latent representation that fully captures the spatio-temporal context of t…

cs.CV20211 cited

Learning to Generate 3D Shapes with Generative Cellular Automata

Dongsu Zhang, Changwoon Choi, Jeonghwan Kim +1

We present a probabilistic 3D generative model, named Generative Cellular Automata, which is able to produce diverse and high quality shapes. We formulate the shape generation proc…

cs.CV202013 cited

Spatial Semantic Embedding Network: Fast 3D Instance Segmentation with Deep Metric Learning

Dongsu Zhang, Junha Chun, Sang Kyun Cha +1

We propose spatial semantic embedding network (SSEN), a simple, yet efficient algorithm for 3D instance segmentation using deep metric learning. The raw 3D reconstruction of an ind…

cs.CV20197 cited

RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion

Muhammad Sarmad, Hyunjoo Jenny Lee, Young Min Kim

We present RL-GAN-Net, where a reinforcement learning (RL) agent provides fast and robust control of a generative adversarial network (GAN). Our framework is applied to point cloud…